CN116502870B - Scheduling policy determination method, device, management terminal and storage medium - Google Patents

Scheduling policy determination method, device, management terminal and storage medium Download PDF

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CN116502870B
CN116502870B CN202310752780.4A CN202310752780A CN116502870B CN 116502870 B CN116502870 B CN 116502870B CN 202310752780 A CN202310752780 A CN 202310752780A CN 116502870 B CN116502870 B CN 116502870B
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徐璞
甄国龙
夏信
何传亮
张博
张亚州
刘永萍
李金龙
刘阳
齐峰
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Beijing Dianke Zhixin Technology Co ltd
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Abstract

The embodiment of the specification provides a scheduling policy determining method, a scheduling policy determining device, a management terminal and a storage medium. The method is applied to the detection service scheduling management terminal, and the detection service scheduling management terminal is connected with at least one detection platform body of a detection place, and comprises the following steps: providing a detection service scheduling management interface; determining relevant information to be detected of the equipment to be detected by responding to information input operation of the equipment to be detected through a detection service scheduling management interface; the information related to the detection comprises a detection item of the detection equipment; according to the item to be detected, a detection scheduling model which obeys detection preset rules is constructed; the detection preset rule is used for agreeing on the detection relation between the equipment to be detected and the detection platform body; the detection scheduling model is used for generating an initial scheduling strategy set; and determining a target scheduling strategy according to the initial scheduling strategy set, so that the utilization rate of the detection platform body can be improved and the total detection time length of the plurality of to-be-detected devices can be optimized when the plurality of to-be-detected devices are detected.

Description

Scheduling policy determination method, device, management terminal and storage medium
Technical Field
The embodiment in the specification relates to the technical field of equipment detection, in particular to a scheduling policy determining method, a scheduling policy determining device, a scheduling policy managing terminal and a storage medium.
Background
The detection laboratory can provide various detection platforms, and correspondingly detect various to-be-detected devices according to related regulations, standards or defined rules or criteria, and when detecting various different to-be-detected devices, a corresponding scheduling strategy needs to be formulated to reasonably allocate the corresponding detection platforms for the to-be-detected devices for detection.
In the related art, the allocation of the detection platform body is generally performed according to the time of delivering the to-be-detected equipment sequentially or the required service time, so as to determine the scheduling policy, and the to-be-detected equipment delivered first is preferentially detected or the to-be-detected equipment with the required service time being short is preferentially detected. However, when detecting for a plurality of devices to be detected, the utilization rate of the detection platform body by the scheduling strategies needs to be improved.
Disclosure of Invention
In view of this, various embodiments of the present disclosure are directed to providing a scheduling policy determining method, apparatus, management terminal, and storage medium to improve the utilization rate of a detection platform, thereby optimizing the total detection time length of a plurality of devices to be detected.
The embodiment of the specification provides a scheduling policy determining method, which is applied to a detection service scheduling management terminal, wherein the detection service scheduling management terminal is connected with at least one detection platform body of a detection place, and the method comprises the following steps: providing a detection service scheduling management interface; determining relevant information to be detected of the equipment to be detected by responding to information input operation of the equipment to be detected through the detection service scheduling management interface; wherein the relevant information to be detected comprises items to be detected of the equipment to be detected; according to the item to be detected, a detection scheduling model which obeys detection preset rules is constructed; the detection preset rule is used for agreeing on a detection relation between the equipment to be detected and the detection platform body; the detection scheduling model is used for generating an initial scheduling strategy set; and determining a target scheduling strategy according to the initial scheduling strategy set.
Further, the determining a target scheduling policy according to the initial scheduling policy set includes: optimizing the initial scheduling strategy set based on the selection operation and the cross operation of the genetic algorithm to obtain an optimized scheduling strategy set; performing tabu search on any one of the optimal scheduling strategies in the optimal scheduling strategy set to obtain candidate optimal scheduling strategies corresponding to the any one of the optimal scheduling strategies; and carrying out replacement operation on any one of the optimal scheduling strategies based on the candidate optimal scheduling strategies to obtain a replaced optimal scheduling strategy set serving as an initial scheduling strategy set.
Preferably, the replacing operation is performed on any one of the optimal scheduling policies based on the candidate optimal scheduling policies to obtain a replaced optimal scheduling policy set, including: determining a target optimal scheduling strategy for replacing any optimal scheduling strategy in the candidate optimal scheduling strategies; and replacing any one of the optimal scheduling strategies by using the target optimal scheduling strategy to obtain a replaced optimal scheduling strategy set.
Further, before the determining the target scheduling policy, the method further includes: constructing an objective function of the detection scheduling model; the parameters of the objective function comprise an arrival time parameter, a detection duration parameter, a starting detection time parameter and a detection sequence parameter; the determining a target scheduling policy according to the initial scheduling policy set includes: optimizing the initial scheduling strategy set based on the objective function to obtain an optimized scheduling strategy set; and determining the target scheduling strategy according to the optimized scheduling strategy set.
Preferably, the information related to the to-be-detected further includes an arrival time of the to-be-detected device to the detection place; the initial scheduling strategy in the initial scheduling strategy set is used for representing the starting detection moment of any one to-be-detected device at any detection platform body; the initial scheduling strategy comprises the detection sequence of any one piece of equipment to be detected on any detection platform body; the optimizing the initial scheduling policy set based on the objective function to obtain an optimized scheduling policy set includes: aiming at any one of the devices to be detected in each initial scheduling strategy, if the service item of the detection platform body where the any one of the devices to be detected is judged to be in accordance with the item to be detected of the any one of the devices to be detected, calculating the detection sequence included in each initial scheduling strategy, the arrival time of the any one of the devices to be detected, the item detection duration of the any one of the devices to be detected and the starting detection time of the any one of the devices to be detected through the objective function to obtain the fitness value of the each initial scheduling strategy; and optimizing the initial scheduling strategy set according to the fitness value of each initial scheduling strategy to obtain the optimized scheduling strategy set.
Preferably, the optimizing the initial scheduling policy set according to the fitness value of each initial scheduling policy to obtain the optimized scheduling policy set includes: determining an optimal initial scheduling strategy in the initial scheduling strategy set according to the fitness value of each initial scheduling strategy; if the iteration times do not reach the preset time threshold, selecting at least part of initial scheduling strategies in the initial scheduling strategy set and the optimal initial scheduling strategy to form a cross scheduling strategy set; performing cross operation based on the cross scheduling policy set to obtain a variation scheduling policy which corresponds to any one of the initial scheduling policies in the cross scheduling policy set one by one; and if the variation scheduling policy meets the detection preset rule, replacing the cross scheduling policy set in the initial scheduling policy set with the variation scheduling policy to obtain the optimized scheduling policy set.
Preferably, the objective function is expressed in the form:
wherein ,Fthe function of the object is represented by a function of the object,i=（1,2，……，I）∈Brepresenting a collection of test tables;j=（1,2，……S）∈Vrepresenting a set of devices to be inspected;k=（1,2，……S）∈Urepresenting the detection sequence of the equipment to be detected; C ij Representing equipment to be inspectedjIn-detection table bodyiDetecting the required detection time length;m j representing equipment to be inspectedjStarting detection time for starting detection;A j representing equipment to be inspectedjArrival time at the detection location;x ijk =1 indicates that the sample is detected in the tableiGo up equipment of waiting to examinejIs the firstkAnd do the detection otherwisex ijk =0。
Preferably, the objective function representation aims at minimizing the waiting time and the detection time of all the devices to be detected at the detection place; the objective function is also expressed in the following form:
wherein ,Fthe function of the object is represented by a function of the object,i=（1,2，……，I）∈Brepresenting a collection of test tables;j=（1,2，……S）∈Vrepresenting a set of devices to be inspected;k=（1,2，……S）∈Urepresenting the detection sequence of the equipment to be detected;S i indicating the detection tableiThe number of devices to be detected;C ij representing equipment to be inspectedjIn-detection table bodyiDetecting the required detection time length;T i indicating the starting idle time of the detection platform body;A j representing equipment to be inspectedjArrival time at the detection location;x ijk =1 indicates that the sample is detected in the tableiGo up equipment of waiting to examinejIs the firstkAnd do the detection otherwisex ijk =0；y ijk Is shown on the detection platformiAnd (4) the idle time between the detection of the (K-1) th device to be detected and the detection of the K-th device to be detected is completed.
Further, the detection preset rule is used for determining constraint conditions of the objective function; the detection preset rule comprises the following steps: the detection duration of each device to be detected depends on the item to be detected; each detection platform body detects one device to be detected at a time; each device to be detected is detected once in the same detection item; the to-be-detected items of each to-be-detected device meet the service items provided by the detection platform body.
Further, the constructing a detection scheduling model according to the to-be-detected item, wherein the detection scheduling model complies with a detection preset rule, and the method comprises the following steps: acquiring detection platform state information and detection site environment information; and constructing a detection scheduling model which complies with detection preset rules according to the detection platform body state information, the detection place environment information and the items to be detected.
The embodiment of the specification provides a scheduling policy determining device, which is applied to a detection service scheduling management terminal, wherein the detection service scheduling management terminal is connected with at least one detection platform body of a detection place, and the device comprises: the management interface providing module is used for providing a detection service scheduling management interface; the to-be-detected information determining module is used for determining to-be-detected related information of to-be-detected equipment according to the information input operation of the to-be-detected equipment through the detection service scheduling management interface; wherein the relevant information to be detected comprises items to be detected of the equipment to be detected; the scheduling model construction module is used for constructing a detection scheduling model which complies with detection preset rules according to the item to be detected; the detection preset rule is used for agreeing on a detection relation between the equipment to be detected and the detection platform body; the detection scheduling model is used for generating an initial scheduling strategy set; and the scheduling policy determining module is used for determining a target scheduling policy according to the initial scheduling policy set.
Preferably, the scheduling policy determining module is further configured to optimize the initial scheduling policy set based on a selection operation and a crossover operation of a genetic algorithm, so as to obtain an optimized scheduling policy set; performing tabu search on any one of the optimal scheduling strategies in the optimal scheduling strategy set to obtain candidate optimal scheduling strategies corresponding to the any one of the optimal scheduling strategies; and carrying out replacement operation on any one of the optimal scheduling strategies based on the candidate optimal scheduling strategies to obtain a replaced optimal scheduling strategy set serving as an initial scheduling strategy set.
The embodiment of the specification provides a detection service scheduling management terminal, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the scheduling policy determining method in any embodiment when executing the computer program.
The embodiment of the present specification provides a detection service scheduling management terminal, the terminal including: the man-machine interaction unit is used for providing a detection service scheduling management interface; the main control unit is connected with the man-machine interaction unit and comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the scheduling policy determining method in any one of the embodiments when executing the computer program; the debugging interface unit is connected with the main control unit and used for connecting at least one detection platform body and/or at least one device to be detected.
The present description provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the scheduling policy determination method according to any one of the above embodiments.
According to the embodiments provided by the specification, the detection service scheduling management interface of the detection service scheduling management terminal connected with the detection platform body of the detection place can be provided, the relevant information to be detected of the equipment to be detected including the item to be detected can be obtained, the detection scheduling model which obeys the detection preset rule is constructed according to the item to be detected, and the initial scheduling strategy set is generated according to the detection scheduling model, so that the target scheduling strategy is determined according to the initial scheduling strategy set, and therefore, when the plurality of pieces of equipment to be detected are detected, the utilization rate of the detection platform body can be improved, and the total detection time length of the plurality of pieces of equipment to be detected is optimized.
Drawings
Fig. 1 is a schematic diagram of a flow of a scheduling policy determining method according to an embodiment of the present disclosure.
Fig. 2 is a schematic diagram of a flow of a method for constructing a detection scheduling model according to an embodiment of the present disclosure.
Fig. 3 is a schematic diagram of a flow of a scheduling policy determining method according to an embodiment of the present disclosure.
Fig. 4 is a schematic diagram of a flow of a method for determining an optimal scheduling policy set according to an embodiment of the present disclosure.
Fig. 5 is a schematic diagram of a flow of a scheduling policy determining method according to an embodiment of the present disclosure.
Fig. 6 is a schematic diagram of a flow of a method for determining an optimal scheduling policy set according to an embodiment of the present disclosure.
Fig. 7 is a schematic diagram of a flow of a method for determining an optimal scheduling policy set according to an embodiment of the present disclosure.
Fig. 8 is a schematic diagram of a flow of a scheduling policy determining method according to an embodiment of the present disclosure.
Fig. 9 is a schematic diagram of a scheduling policy determining apparatus provided in an embodiment of the present disclosure.
Fig. 10 is a schematic diagram of a detection service scheduling management terminal according to an embodiment of the present disclosure.
Fig. 11 is a schematic diagram of a detection service scheduling management terminal according to an embodiment of the present disclosure.
Fig. 12 is a schematic diagram of a detection service scheduling management terminal according to an embodiment of the present disclosure.
Fig. 13 is a schematic diagram of a detection service scheduling management terminal according to an embodiment of the present disclosure.
Detailed Description
In order to make the technical solution of the present specification better understood by those skilled in the art, the technical solution of the present specification embodiment will be clearly and completely described below with reference to the accompanying drawings in the embodiment of the present specification, and it is apparent that the described embodiment is only a part of the embodiment of the present specification, but not all the embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are intended to be within the scope of the present disclosure.
The detection laboratory can provide various detection platforms, and carries out corresponding detection on various to-be-detected devices according to related regulations, standards or defined rules or criteria, and when detecting various different to-be-detected devices, a corresponding scheduling strategy is required to be formulated so as to reasonably allocate the corresponding detection platforms for the to-be-detected devices for detection.
In the related art, the allocation of the detection platform body is generally performed according to the time of delivering the to-be-detected equipment sequentially or the required service time, so as to determine the scheduling policy, and the to-be-detected equipment delivered first is preferentially detected or the to-be-detected equipment with the required service time being short is preferentially detected.
Common scheduling algorithms typically include First come First served (First Come First Served, FCFS), short Job First, SJF, high response ratio First scheduling (Highest Response Ratio Next, HRRN), and the like. The first-come first-serve algorithm is used for serving according to the sequence of the operation/process, and when the scheduling algorithm is used for scheduling, a long time is needed for waiting for short detection services arranged after long detection services. The short job priority scheduling algorithm is an algorithm for scheduling short jobs or short processes preferentially, and each process is associated with its estimated running time to select the job with the shortest estimated calculation time to put into operation, but is less advantageous to long detection jobs, and if short jobs continue to join in a ready queue, long jobs can not be served for a longer time. The high-response-ratio priority scheduling algorithm is an algorithm for allocating the response ratio, and is a compromise algorithm between a first-come first-serve algorithm and a short-job priority scheduling algorithm, and not only considers job waiting time but also considers job running time, and not only considers short jobs but also does not make the long job waiting time overlong. However, when detecting a plurality of devices to be detected, the scheduling strategies are determined according to fairness, average waiting time or average waiting time as indexes, and the utilization rate of a detection platform body needs to be improved, so that the detection time is long.
For some power electronics laboratories and intelligent laboratories, the detection places of the power electronics laboratories and intelligent laboratories can be provided with a plurality of types/numbers of detection platforms, when a certain batch of equipment to be detected is required to be detected, the detection platforms are reasonably allocated or scheduled for each of the equipment to be detected according to the arrival time, the item to be detected, the detection duration and the like of each of the equipment to be detected, so that the utilization rate of the detection platforms in the detection places is improved, the total detection duration of the batch of equipment to be detected is reduced, the detection efficiency of the batch of equipment to be detected is improved, the waiting duration of users to which the equipment to be detected belongs is reduced, and the operation cost of the detection platforms in the detection places is reduced.
The embodiment of the specification provides a detection service scheduling management system, which can comprise a detection service scheduling management terminal and at least one detection platform body connected with the detection service scheduling management terminal.
Referring to fig. 1, fig. 1 is a schematic flow chart of a scheduling policy determining method according to the present embodiment, where the method includes steps according to the present embodiment, but may include more or less steps based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one implementation of a plurality of step execution orders and does not represent a unique execution order. In actual system or server product execution, the methods illustrated in the embodiments may be performed sequentially or in parallel (e.g., in parallel processors or in the context of multi-threaded processing). The scheduling policy determining method can be applied to a detection service scheduling management terminal in a detection service management system, and specifically as shown in fig. 1, the scheduling policy determining method can include the following steps.
Step S110: and providing a detection service scheduling management interface.
In some cases, when the equipment to be detected is detected, the relevant information to be detected of the equipment to be detected can be acquired first, a target scheduling strategy corresponding to the equipment to be detected is determined based on the relevant information to be detected, and then a corresponding detection platform body is distributed to the equipment to be detected based on the target scheduling strategy so as to detect the equipment to be detected. In this embodiment, the detection service scheduling management terminal may provide a detection service scheduling management interface, so that a detection person or a worker can enter relevant information to be detected of a plurality of devices to be detected through the detection service scheduling management interface. The information related to the to-be-detected may refer to information of each to-be-detected device involved in determining the target scheduling policy for the plurality of to-be-detected devices.
Step S120: determining relevant information to be detected of the equipment to be detected by responding to information input operation of the equipment to be detected through a detection service scheduling management interface; the information related to the to-be-detected comprises to-be-detected items of to-be-detected equipment.
In this embodiment, the information about the to-be-inspected device may be determined by detecting the information input operation of the to-be-inspected device by the service scheduling management interface. Specifically, for example, the detection service scheduling management interface may be preset with an information input control, and the detection service scheduling management terminal may determine information about to be detected of the plurality of devices to be detected in response to an information input operation of the information input control. The information entry control and the information entry operation may be a selection control and a corresponding selection operation, or an input control and a corresponding input operation, respectively, for example. As an example, a to-be-inspected item of any to-be-inspected device may be determined from a plurality of preset to-be-inspected items in response to a selection operation of a selection control. As an example, input information of the to-be-detected item may be obtained in response to an input operation of the input control, the to-be-detected item may be searched in a plurality of preset to-be-detected items based on the input information of the to-be-detected item, and a preset to-be-detected item matched with the input information of the to-be-detected item in the plurality of preset to-be-detected items may be used as the to-be-detected item of any to-be-detected device. Of course, the detection service scheduling management interface can also respond to information input operation in other modes, so as to determine the relevant information to be detected of any piece of equipment to be detected or the items to be detected in the relevant information to be detected.
Step S130: according to the item to be detected, a detection scheduling model which obeys detection preset rules is constructed; the detection preset rule is used for agreeing on the detection relation between the equipment to be detected and the detection platform body; the detection scheduling model is used to generate an initial set of scheduling policies.
In this embodiment, a detection scheduling model that adheres to a detection preset rule may be constructed according to a to-be-detected item of the to-be-detected device, and an initial scheduling policy set of the to-be-detected device may be generated based on the detection scheduling model. Specifically, a detection scheduling model capable of generating an initial scheduling policy can be constructed according to-be-detected items of a plurality of to-be-detected devices and preset detection preset rules, and a specified number of initial scheduling policies are generated through the detection scheduling model, so that an initial scheduling policy set is obtained. The initial scheduling policy in the initial scheduling policy set can be used for representing the starting detection time of any one device to be detected at any one detection platform, and the initial scheduling policy comprises the detection sequence of any one device to be detected at any one detection platform. The designated number of the initial scheduling policies in the initial scheduling policy set may be determined according to actual situations, for example, may be determined according to the total number of devices to be checked.
Step S140: and determining a target scheduling strategy according to the initial scheduling strategy set.
In this embodiment, after the initial scheduling policy set is determined, the target scheduling policy of the device to be inspected may be determined according to the initial scheduling policy set. Specifically, each initial scheduling policy in the initial scheduling policy set may be evaluated and optimized, so as to determine a target scheduling policy with the shortest total detection duration.
In the above embodiment, the detection service scheduling management terminal connected with the detection platform body of the detection location is provided, and the relevant information to be detected including the item to be detected of the equipment to be detected can be obtained through the detection service scheduling management interface of the terminal, the detection scheduling model which obeys the detection preset rule is constructed according to the item to be detected, and the initial scheduling policy set is generated according to the detection scheduling model, so that the target scheduling policy can be determined according to the initial scheduling policy set, and thus, when a plurality of pieces of equipment to be detected are detected, the target scheduling policy with the shortest total detection duration can be obtained, thereby improving the utilization rate of the detection platform body and optimizing the total detection duration of a plurality of pieces of equipment to be detected. Meanwhile, the waiting time of the user of the equipment to be detected is reduced, and the operation cost of the detection platform body in the detection place is reduced.
In some embodiments, referring to fig. 2, constructing a detection scheduling model that complies with detection preset rules according to the item to be detected may include the following steps.
Step S210: and acquiring detection platform state information and detection place environment information.
In some cases, the detection scheduling model may be built based on the environment of the detection venue and the detection capabilities that the detection venue is capable of providing.
In the present embodiment, the detection service scheduling management terminal may acquire detection stage state information of any one of the detection stages connected thereto in the detection site, and may acquire detection site environment information of the detection site. The detection platform state information may include a working state, an idle state, a normal state, a fault state, and the like of the detection platform, and the detection site environment information may include temperature and humidity information, power consumption state information, and the like of the detection site.
Step S220: and constructing a detection scheduling model which complies with detection preset rules according to the detection platform state information, the detection place environment information and the items to be detected.
In this embodiment, after the detection platform state information and the detection location environment information are acquired, a detection scheduling model that complies with a detection preset rule may be constructed according to the detection platform state information and the detection location environment information in combination with a to-be-detected item of any to-be-detected device. Specifically, when it is determined that the detection table body meets the preset state according to the state information of the detection table body and the detection place meets the preset environment information according to the environment information of the detection place, a detection scheduling model which complies with the detection preset rule can be built according to the item to be detected. For example, a detection platform body in a normal state or an idle state may be used as a detection platform body capable of scheduling or distributing before the detection of the device to be detected starts, and the detection platform body in a fault state or an operating state may not participate in the detection of the device to be detected, that is, a detection scheduling model may be constructed based on the detection platform body in the normal state or the idle state. For example, before the device to be detected starts to detect, whether the temperature and the humidity of the detection place are within the preset temperature and humidity range or not may be determined, and the detection scheduling model may be built when the temperature and the humidity of the detection place are determined to be within the preset temperature and humidity range. For example, it may be further determined whether the power consumption state of the detection site or the power consumption state of any one of the detection platforms satisfies the preset power consumption state based on the power consumption state information, and if the preset power consumption state is satisfied, the detection scheduling model may be constructed.
In the above embodiment, by acquiring the state information of the detection platform and the environment information of the detection location, when it is determined that the detection platform meets the preset state according to the state information of the detection platform and the detection location meets the preset environment information according to the environment information of the detection location, a detection scheduling model that complies with the detection preset rule is constructed according to the item to be detected, and then a target scheduling policy of the device to be detected is determined based on the detection scheduling model, and a plurality of devices to be detected are detected according to the target scheduling policy. According to the embodiment, the detection table bodies can be dynamically distributed to the plurality of to-be-detected devices, so that the artificial interference is reduced, and the utilization rate of the detection table bodies in the detection place is improved.
In some embodiments, referring to fig. 3, determining a target scheduling policy from an initial set of scheduling policies may include the following steps.
Step S310: and optimizing the initial scheduling strategy set based on the selection operation and the cross operation of the genetic algorithm to obtain an optimized scheduling strategy set.
In some cases, the initial scheduling policy set generated by the detection scheduling model may be optimized based on a genetic algorithm and a tabu search algorithm to determine a target scheduling policy with the shortest total detection duration.
In this embodiment, the initial scheduling policy set may be optimized based on a selection operation and a crossover operation of the genetic algorithm, to obtain an optimized scheduling policy set. Specifically, for example, an initial scheduling policy set including a specified number of initial scheduling policies may be obtained by randomly generating the specified number of initial scheduling policies by detecting the scheduling model, and the initial scheduling policy set may be optimized based on a selection operation and a crossover operation of the genetic algorithm, so as to obtain an optimized scheduling policy set corresponding to the initial scheduling policy set.
Step S320: and performing tabu search on any one of the optimal scheduling strategies in the optimal scheduling strategy set to obtain candidate optimal scheduling strategies corresponding to the any one of the optimal scheduling strategies.
In this embodiment, after the initial scheduling policy is optimized based on the genetic algorithm to obtain the optimized scheduling policy set, in order to improve the performance of avoiding detour search that is optimized based on the genetic algorithm, hybrid optimization may be performed in combination with a tabu search algorithm, so as to achieve rapid global optimization. Specifically, for example, after the initial scheduling policy is optimized based on the genetic algorithm to obtain an optimized scheduling policy set, a tabu search can be performed for any one of the optimized scheduling policies in the optimized scheduling policy set to obtain a candidate optimized scheduling policy corresponding to the any one of the optimized scheduling policies.
Step S330: and carrying out replacement operation on any optimized scheduling strategy based on the candidate optimized scheduling strategy to obtain a replaced optimized scheduling strategy set which is used as an initial scheduling strategy set.
In this embodiment, after determining the candidate optimal scheduling policy of the optimal scheduling policy, the candidate optimal scheduling policy may be used to replace the optimal scheduling policy corresponding to the candidate optimal scheduling policy, so as to obtain a replaced optimal scheduling policy set, and the replaced optimal scheduling policy set is used as an initial scheduling policy set to continue iterative optimization.
In some embodiments, referring to fig. 4, performing a replacement operation on any one of the optimized scheduling policies based on the candidate optimized scheduling policies to obtain a replaced optimized scheduling policy set may include the following steps.
Step S410: and determining a target optimal scheduling strategy for replacing any optimal scheduling strategy in the candidate optimal scheduling strategies.
In some cases, a tabu search is performed for any one of the set of optimal scheduling policies, and a plurality of candidate optimal scheduling policies may be obtained.
In this embodiment, a target optimal scheduling policy for replacing any one of the optimal scheduling policies may be determined among the candidate optimal scheduling policies. Specifically, the candidate optimal scheduling policy with the shortest total detection time length among the plurality of candidate optimal scheduling policies may be used as the target optimal scheduling policy for replacing the optimal scheduling policy.
Step S420: and replacing any optimal scheduling strategy by using the target optimal scheduling strategy to obtain a replaced optimal scheduling strategy set.
In the above embodiment, the initial scheduling policy set is optimized through a selection operation and a crossover operation based on a genetic algorithm to obtain an optimized scheduling policy set, a tabu search is performed for any one of the optimized scheduling policies in the optimized scheduling policy set to obtain a target optimized scheduling policy for replacing any one of the optimized scheduling policies, and the target optimized scheduling policy is utilized to replace the corresponding optimized scheduling policy to obtain a replaced optimized scheduling policy set, so that global rapid optimization can be performed based on the initial scheduling policy set to obtain the optimized scheduling policy set, and thus the target scheduling policy can be rapidly determined based on the optimized scheduling policy set.
In some embodiments, the scheduling policy determining method may further include: and constructing an objective function of the detection scheduling model.
In this embodiment, before determining the target scheduling policy, an objective function of the detection scheduling model may be constructed, so that any one of the initial scheduling policies in the initial scheduling policy set may be evaluated and optimized, thereby determining the target scheduling policy. Specifically, the parameters of the objective function may include an arrival time parameter, a detection duration parameter, a start detection time parameter, and a detection order parameter. The arrival time parameter is used for describing the time when any one of the devices to be detected arrives at the detection place, the detection time parameter is used for describing the detection time of any one of the devices to be detected on any one of the detection platforms in the detection place, the starting detection time parameter is used for describing the time when any one of the devices to be detected starts to be detected at the detection place, and the detection sequence parameter is used for describing the detection sequence number of any one of the devices to be detected or the detection sequence number on any one of the detection platforms.
In some embodiments, the objective function may be represented using equation 1:
equation 1
wherein ,Frepresenting an objective function, and representing the total detection time length of all the equipment to be detected in the detection place;i=（1,2，……，I）∈Brepresenting a collection of test tables;j=（1,2，……S）∈Vrepresenting a set of devices to be inspected;k=（1,2，……S）∈Urepresenting the detection sequence of the equipment to be detected;C ij representing equipment to be inspectedjIn-detection table bodyiDetecting the required detection time length;m j representing equipment to be inspectedjStarting detection time for starting detection;A j representing equipment to be inspectedjArrival time at the detection location;x ijk =1 indicates that the sample is detected in the tableiGo up equipment of waiting to examinejIs the firstkAnd do the detection otherwisex ijk =0。
In some embodiments, the total detection duration of all the devices to be detected at the detection location may be determined based on the waiting duration and the detection duration of each device to be detected at the detection location, and thus, the objective function may be represented with the objective of minimizing the waiting duration and the detection duration of all the devices to be detected at the detection location.
In some cases, the total detection duration=opening detection time-arrival time-detection duration of the detection table body of each device to be detected, and the induction method is adopted to derive the formula 1, so that the formula 2 can be obtained. In this embodiment, the objective function can also be expressed by using equation 2.
Equation 2
wherein ,S i indicating the detection tableiThe number of devices to be detected;T i indicating the starting idle time of the detection platform body;y ijk is shown on the detection platformiAnd (4) the idle time between the detection of the (K-1) th device to be detected and the detection of the K-th device to be detected is completed.
In this embodiment, when constructing an objective function of the detection scheduling model, it is necessary to determine constraint conditions of the objective function. Illustratively, the constraints of the objective function may include:
（1）；
（2）；
（3）。
wherein ,representing that the sum of the to-be-detected devices on each detection platform body is equal to the total number of the to-be-detected devices; />Indicating that each device to be inspected must be inspected once on a certain inspection bench; />Indicating that the device to be inspected can be inspected on the inspection bench.
In some embodiments, constraints of the objective function may be determined based on detecting preset rules. Specifically, for example, detecting the preset rule may include: (1) The detection duration of each device to be detected depends on the item to be detected; (2) each detection platform detects one device to be detected at a time; (3) Each device to be detected is detected once in the same detection item; (4) The to-be-detected items of each to-be-detected device meet the service items provided by the detection platform body.
In some embodiments, referring to fig. 5, determining a target scheduling policy from an initial set of scheduling policies may include the following steps.
Step S510: and optimizing the initial scheduling strategy set based on the objective function to obtain an optimized scheduling strategy set.
In this embodiment, the initial scheduling policy set may be optimized based on the objective function, to obtain an optimized scheduling policy set. Specifically, for example, each initial scheduling policy in the initial scheduling policy set may be evaluated based on an objective function, an initial scheduling policy with the shortest total detection duration is determined from the initial scheduling policy set according to an evaluation result, and then any one of the initial scheduling policies in the initial scheduling policy set is optimized based on the initial scheduling policy with the shortest total detection duration in the initial scheduling policy set, so as to obtain an optimized scheduling policy set.
Step S520: and determining a target scheduling strategy according to the optimized scheduling strategy set.
In this embodiment, the target scheduling policy may be determined according to the optimized scheduling policy set. Specifically, for example, after the initial scheduling policy set is optimized and the optimized scheduling policy set is obtained, an optimized scheduling policy with the shortest total detection duration may be determined from the optimized scheduling policy set based on an objective function, and may be used as the target scheduling policy.
In the above embodiment, the initial scheduling policy set is optimized based on the objective function to obtain an optimized scheduling policy set, and the objective scheduling policy is determined according to the optimized scheduling policy set, so that the objective scheduling policy with the shortest total detection duration can be obtained from the optimized scheduling policy set.
In some embodiments, referring to fig. 6, optimizing the initial set of scheduling policies based on the objective function to obtain an optimized set of scheduling policies may include the following steps.
Step S610: and aiming at any one of the to-be-detected devices in each initial scheduling strategy, if the service item of the detection platform where any one of the to-be-detected devices is judged to be in accordance with the to-be-detected item of any one of the to-be-detected devices, calculating the detection sequence included in each initial scheduling strategy, the arrival time of any one of the to-be-detected devices, the item detection duration of any one of the to-be-detected devices and the starting detection time of any one of the to-be-detected devices through an objective function to obtain the fitness value of each initial scheduling strategy.
Any initial scheduling strategy of the initial scheduling strategy set comprises the detection sequence of any one piece of equipment to be detected in any detection platform body and the starting detection moment of any piece of equipment to be detected. In addition, the relevant information to be detected can also comprise the arrival time of the equipment to be detected to the detection place.
In some cases, the initial scheduling policy set may be optimized based on the fitness value, and whether each initial scheduling policy in the initial scheduling policy set meets a detection preset rule may be determined, where the fitness value of each initial scheduling policy is determined based on an objective function.
In this embodiment, for any one of the devices to be detected in each initial scheduling policy, it may be determined whether a service item of a detection platform body where the device to be detected is located meets a item to be detected of the device to be detected, if it is determined that the service item of the detection platform body where each of the devices to be detected in the initial scheduling policy is located meets a corresponding item to be detected, a detection sequence included in the initial scheduling policy, an arrival time of any one of the devices to be detected, a project detection time of any one of the devices to be detected, and a start detection time of any one of the devices to be detected are calculated by an objective function, so as to obtain a corresponding objective function value, and convert the objective function value into a corresponding fitness value. And if the service item of the detection platform body where any one of the to-be-detected devices is positioned in the initial scheduling strategy is judged to be not in accordance with the corresponding to-be-detected item, setting the adaptability of the initial scheduling strategy to be zero. Illustratively, the objective function value is inversely proportional to the magnitude of the fitness value.
Step S620: and optimizing the initial scheduling strategy set according to the fitness value of each initial scheduling strategy to obtain an optimized scheduling strategy set.
In this embodiment, the initial scheduling policy set may be optimized according to the fitness value of each initial scheduling policy, to obtain an optimized scheduling policy set. Specifically, for example, each initial scheduling policy in the initial scheduling policy set may be evaluated based on the fitness value, an initial scheduling policy with the greatest fitness is determined from the initial scheduling policy set, and then the initial scheduling policy with the greatest fitness and any other initial scheduling policy in the initial scheduling policy set are optimized based on the initial scheduling policy with the greatest fitness, so as to obtain an optimized scheduling policy set.
In the above embodiment, the fitness value of each initial scheduling policy is determined by detecting the preset rule and the objective function, and the initial scheduling policy set is optimized according to the fitness value, so that the optimized scheduling policy set can be obtained.
In some embodiments, referring to fig. 7, optimizing the initial scheduling policy set according to the fitness value of each initial scheduling policy to obtain an optimized scheduling policy set may include the following steps.
Step S710: and determining an optimal initial scheduling strategy in the initial scheduling strategy set according to the adaptability value of each initial scheduling strategy.
In this embodiment, the optimal initial scheduling policy may be determined in the initial scheduling policy set according to the fitness value of each initial scheduling policy. Specifically, for example, the fitness value of each initial scheduling policy in the initial scheduling policy set may be compared, and the initial scheduling policy with the largest fitness value may be determined as the optimal initial scheduling policy. That is, the initial scheduling policy having the shortest total detection time length in the initial scheduling policy set is determined as the optimal initial scheduling policy.
Step S720: and if the iteration times do not reach the preset times threshold, selecting at least part of initial scheduling strategies in the initial scheduling strategy set and the optimal initial scheduling strategy to form a cross scheduling strategy set.
In some cases, the optimization process of the initial set of scheduling policies is an iterative optimization process.
In this embodiment, after determining the optimal initial scheduling policy in the initial scheduling policy set, the iteration number may be determined, and if the iteration number does not reach the preset number threshold, at least a portion of the initial scheduling policies in the initial scheduling policy set and the optimal initial scheduling policy may be selected to form a cross scheduling policy set, so that the initial scheduling policy set may be optimized based on the cross scheduling policy set.
Step S730: and performing cross operation based on the cross scheduling policy set to obtain a variation scheduling policy which corresponds to any one of the initial scheduling policies in the cross scheduling policy set one by one.
In this embodiment, after determining the cross scheduling policy set based on the initial scheduling policy set, the cross operation may be performed based on the cross scheduling policy set, so as to obtain a variant scheduling policy corresponding to any one of the initial scheduling policies in the cross scheduling policy set. Specifically, for example, the optimal initial scheduling policy in the cross scheduling policy set may be respectively cross-operated with the initial scheduling policies in the cross scheduling policy set, so as to obtain a variant scheduling policy corresponding to any one of the initial scheduling policies in the cross scheduling policy set. The interleaving operation may be a single point interleaving operation, for example.
Step S740: if the variation scheduling policy meets the detection preset rule, replacing the cross scheduling policy set in the initial scheduling policy set with the variation scheduling policy to obtain an optimized scheduling policy set.
In some cases, any one of the initial scheduling policies in the cross scheduling policy set is cross-operated, or, in other words, the optimal initial scheduling policy in the cross scheduling policy set and other initial scheduling policies in the cross scheduling policy set are cross-operated respectively, where the obtained variant scheduling policy may not meet the detection preset rule.
In this embodiment, whether the variable scheduling policy satisfies the detection preset rule may be determined, and if the variable scheduling policy satisfies the detection preset rule, the cross scheduling policy set in the initial scheduling policy set may be replaced with the variable scheduling policy, so as to obtain the optimized scheduling policy set. If the variation scheduling policy does not meet the detection preset rule, at least part of the initial scheduling policies in the initial scheduling policy set and the optimal initial scheduling policy can be reselected to form a cross scheduling policy set, and the cross operation is continued.
The embodiment of the present disclosure provides a scheduling policy determining method, which may be applied to a detection service scheduling management terminal in a detection service management system, referring to fig. 8, and may include the following steps.
Step S802: and providing a detection service scheduling management interface.
Step S804: determining relevant information to be detected of the equipment to be detected by responding to information input operation of the equipment to be detected through a detection service scheduling management interface; the information related to the to-be-detected comprises to-be-detected items of to-be-detected equipment and arrival time of the to-be-detected equipment to the detection place.
Step S806: according to the item to be detected, a detection scheduling model which obeys detection preset rules is constructed; the detection preset rule is used for agreeing on the detection relation between the equipment to be detected and the detection table body.
Step S808: constructing an objective function of a detection scheduling model; the parameters of the objective function comprise an arrival time parameter, a detection duration parameter, a starting detection time parameter and a detection sequence parameter.
Step S810: generating an initial scheduling strategy set according to the detection scheduling model; the initial scheduling strategy in the initial scheduling strategy set is used for representing the starting detection time of any one piece of equipment to be detected at any one detection platform body; the initial scheduling strategy comprises the detection sequence of any device to be detected on any detection platform.
Step S812: and judging whether the service item of the detection platform body where any one of the to-be-detected devices is positioned accords with the to-be-detected item of any one of the to-be-detected devices according to any one of the to-be-detected devices in each initial scheduling strategy.
Step S814: if yes, calculating the detection sequence included in each initial scheduling strategy, the arrival time of any one of the devices to be detected, the project detection time of any one of the devices to be detected and the start detection time of any one of the devices to be detected through an objective function, and obtaining the fitness value of each initial scheduling strategy.
Step S816: and if the initial scheduling strategy is not met, setting the adaptability value of the initial scheduling strategy to be zero.
Step S818: and determining an optimal initial scheduling strategy in the initial scheduling strategy set according to the adaptability value of each initial scheduling strategy.
Step S820: and judging whether the iteration times reach a preset time threshold.
Step S822: and if the iteration times reach a preset time threshold, outputting an optimal initial scheduling strategy as a target scheduling strategy.
Step S824: if the iteration times do not reach the preset times threshold, selecting at least part of initial scheduling strategies in the initial scheduling strategy set and the optimal initial scheduling strategy to form a cross scheduling strategy set; and performing cross operation based on the cross scheduling policy set to obtain a variation scheduling policy which corresponds to any one of the initial scheduling policies in the cross scheduling policy set one by one.
Step S826: if the variation scheduling policy meets the detection preset rule, replacing the cross scheduling policy set in the initial scheduling policy set with the variation scheduling policy to obtain an evolution scheduling policy set.
Step S828: and performing tabu search on any evolutionary scheduling strategy in the evolutionary scheduling strategy set to obtain a candidate evolutionary scheduling strategy corresponding to the any evolutionary scheduling strategy.
Step S830: a target evolutionary schedule strategy for replacing any one of the evolutionary schedule strategies is determined from the candidate evolutionary schedule strategies.
Step S832: and replacing any evolutionary scheduling strategy by using the target evolutionary scheduling strategy to obtain a replaced evolutionary scheduling strategy set which is used as an initial scheduling strategy set.
Specifically, the above scheduling policy optimization step is repeatedly executed until the target scheduling policy is determined.
The embodiment of the specification provides a scheduling policy determining device. The scheduling policy determining device can be applied to a detection service scheduling management terminal, and the detection service scheduling management terminal is connected with at least one detection platform body of a detection place. Referring to fig. 9, the scheduling policy determining apparatus may include a management interface providing module 910, a pending information determining module 920, a scheduling model constructing module 930, and a scheduling policy determining module 940.
The management interface providing module 910 is configured to provide a detection service scheduling management interface. The to-be-detected information determining module 920 is configured to determine to-be-detected related information of the to-be-detected device by detecting an information input operation of the to-be-detected device in response to the service scheduling management interface; the information related to the to-be-detected comprises to-be-detected items of to-be-detected equipment. The scheduling model construction module 930 is configured to construct a detection scheduling model that complies with a detection preset rule according to the item to be detected; the detection preset rule is used for agreeing on the detection relation between the equipment to be detected and the detection platform body; the detection scheduling model is used to generate an initial set of scheduling policies. The scheduling policy determining module 940 is configured to determine a target scheduling policy according to the initial scheduling policy set.
In some embodiments, the scheduling policy determining module 940 may be further configured to optimize the initial scheduling policy set based on a selection operation and a crossover operation of the genetic algorithm, to obtain an optimized scheduling policy set; performing tabu search for any one of the optimal scheduling strategies in the optimal scheduling strategy set to obtain candidate optimal scheduling strategies corresponding to the any one of the optimal scheduling strategies; and carrying out replacement operation on any optimized scheduling strategy based on the candidate optimized scheduling strategy to obtain a replaced optimized scheduling strategy set which is used as an initial scheduling strategy set.
The specific functions and effects achieved by the scheduling policy determining apparatus may be explained with reference to other embodiments of the present specification, and will not be described herein. The respective modules in the scheduling policy determining apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in hardware or independent of a processor in the computer device, or can be stored in a memory in the computer device in a software mode, so that the processor can call and execute the operations corresponding to the modules.
The embodiment of the present disclosure provides a detection service scheduling management terminal, referring to fig. 10, the management terminal may include a memory and a processor, where the memory stores a computer program, and the processor implements the scheduling policy determining method in the above embodiment when executing the computer program.
In one embodiment, the internal structure of the management terminal may be as shown in fig. 10. The management terminal comprises a processor, a memory and a communication interface which are connected through a system bus. Wherein the processor of the management terminal is configured to provide computing and control capabilities. The memory of the management terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the management terminal is used for carrying out wired or wireless communication with external equipment, and the wireless mode can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program, when executed by a processor, implements a scheduling policy determination method.
The embodiment of the present disclosure further provides a detection service scheduling management terminal, referring to fig. 11, where the front surface of the management terminal may be provided with a power button and two USB3.0 interfaces. The power button is a power switch of the management terminal, and the USB3.0 interface is used for connecting external equipment, such as a connection key mouse or a detection platform body.
In one embodiment, referring to fig. 12, the management terminal may include a man-machine interaction unit, a main control unit, and a debug interface unit. The man-machine interaction unit can be used for providing a detection service scheduling management interface; the main control unit is used for being connected with the man-machine interaction unit, and can comprise a memory and a processor, wherein the memory stores a computer program, and the processor realizes the detection service scheduling method when executing the computer program; the debugging interface unit is connected with the main control unit and used for connecting at least one detection platform body and/or at least one device to be detected.
Specifically, referring to fig. 13, the back of the management terminal may include 4 paths of RS485 interfaces, 2 RJ45 network interfaces, and two USB3.0 interfaces, which may be connected to the detection platform. Specifically, the Bluetooth wireless communication device can further comprise an HDMI display interface, a 5G antenna interface, a BT Bluetooth antenna interface, a Beidou antenna interface and a WIFI interface. The RS485 interface is used for connecting a detection platform body with the RS485 interface, monitoring the running state of the detection platform body, and judging whether the detection platform body is currently working or idle by sending or receiving the state of the detection platform body. The network port is used for connecting with a detection platform body with a network interface. The USB3.0 interface is used for connecting a detection platform body with the USB interface. The BT Bluetooth interface is used for connecting with a mobile phone APP or equipment to be inspected. The HDMI interface can be externally connected with a display to display the interface of the management terminal. The 5G antenna interface is used for receiving and transmitting 5G signals and can be connected with a server through a public network. The Beidou antenna interface is used for receiving and sending Beidou positioning information and time service information. The WIFI interface is used for connecting a wireless local area network and can be connected with the detection platform body in a networking mode.
Specifically, the man-machine interaction unit of the management terminal can be connected with the touch screen and is connected with the main control unit through the SPI interface, and the man-machine interaction unit is used for detecting personnel to operate the scheduling management interface and inputting information of equipment to be detected. The Bluetooth communication unit is used for connecting near field communication with the mobile phone and remotely managing the APP. The 5G remote communication unit is connected with the mobile phone through a public network and remotely manages the APP. The Beidou positioning unit: for locating the position information of the management terminal while receiving the standard clock. The RS485 communication unit is used for connecting detection platform body equipment and receiving the state information of the platform body. The WIFI communication unit is used for near field communication with the mobile phone. The main control unit can be used for detecting the state data processing of the platform body and dynamically determining the scheduling strategy. The USB interface is connected with the detection platform body or the equipment to be detected.
In one embodiment, the management terminal comprises a man-machine interaction unit, a Bluetooth communication unit, a 5G remote communication unit, an RS485 communication unit and a WIFI communication unit which are connected with the main control unit through a serial peripheral interface (Serial Peripheral Interface, SPI), wherein the Bluetooth communication unit, the 5G remote communication unit, the RS485 communication unit and the WIFI communication unit can be connected with the main control unit through a USB Hub interface expander.
The present specification embodiment also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a computer, causes the computer to perform the scheduling policy determining method in any of the above embodiments.
The present description also provides a computer program product comprising instructions which, when executed by a computer, cause the computer to perform the scheduling policy determination method of any of the above embodiments.
It will be appreciated that the specific examples herein are intended only to assist those skilled in the art in better understanding the embodiments of the present disclosure and are not intended to limit the scope of the present invention.
It should be understood that, in various embodiments of the present disclosure, the sequence number of each process does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.
It will be appreciated that the various embodiments described in this specification may be implemented either alone or in combination, and are not limited in this regard.
Unless defined otherwise, all technical and scientific terms used in the embodiments of this specification have the same meaning as commonly understood by one of ordinary skill in the art to which this specification belongs. The terminology used in the description is for the purpose of describing particular embodiments only and is not intended to limit the scope of the description. The term "and/or" as used in this specification includes any and all combinations of one or more of the associated listed items. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It will be appreciated that the processor of the embodiments of the present description may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method embodiments may be implemented by integrated logic circuits of hardware in a processor or instructions in software form. The processor may be a general purpose processor, a Digital signal processor (Digital SignalProcessor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), an off-the-shelf programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The methods, steps and logic blocks disclosed in the embodiments of the present specification may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present specification may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory, and the processor reads the information in the memory and, in combination with its hardware, performs the steps of the above method.
It will be appreciated that the memory in the embodiments of this specification may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable Programmable ROM (EPROM), an Electrically Erasable Programmable ROM (EEPROM), or a flash memory, among others. The volatile memory may be Random Access Memory (RAM). It should be noted that the memory of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present specification.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system, apparatus and unit may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in this specification, it should be understood that the disclosed systems, apparatuses, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment.
In addition, each functional unit in each embodiment of the present specification may be integrated into one processing unit, each unit may exist alone physically, or two or more units may be integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present specification may be essentially or portions contributing to the prior art or portions of the technical solutions may be embodied in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present specification. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a read-only memory (ROM), a random-access memory (RAM), a magnetic disk, or an optical disk, etc.
The foregoing is merely specific embodiments of the present disclosure, but the scope of the present disclosure is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope disclosed in the present disclosure, and should be covered by the scope of the present disclosure. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (12)

1. A scheduling policy determining method, which is applied to a detection service scheduling management terminal, wherein the detection service scheduling management terminal is connected with at least one detection platform body of a detection place, and the method comprises:
providing a detection service scheduling management interface;
determining to-be-detected related information of a plurality of to-be-detected devices through the detection service scheduling management interface in response to information input operation of the to-be-detected devices; the to-be-detected related information comprises to-be-detected items of to-be-detected equipment and arrival time of the to-be-detected equipment to the detection place;
according to the item to be detected, a detection scheduling model which obeys detection preset rules is constructed; the detection preset rule is used for agreeing on a detection relation between the equipment to be detected and the detection platform body; the detection scheduling model is used for generating an initial scheduling strategy set;
constructing an objective function of the detection scheduling model; the parameters of the objective function comprise an arrival time parameter, a detection duration parameter, a starting detection time parameter and a detection sequence parameter; the arrival time parameter is used for describing the arrival time;
determining a target scheduling strategy according to the initial scheduling strategy set; wherein, the determining a target scheduling policy according to the initial scheduling policy set includes: optimizing the initial scheduling strategy set based on the objective function to obtain an optimized scheduling strategy set; determining the target scheduling strategy according to the optimized scheduling strategy set;
The objective function representation aims at minimizing the waiting time and the detection time of all the equipment to be detected in the detection place, and the objective function representation adopts any one of the following forms:
wherein ,Fthe function of the object is represented by a function of the object,i=（1,2，……，I）∈Brepresenting a collection of test tables;j=（1,2，……S）∈Vrepresenting a set of devices to be inspected;k=（1,2，……S）∈Urepresenting the detection sequence of the equipment to be detected;C ij representing equipment to be inspectedjIn-detection table bodyiDetecting the required detection time length;m j representing equipment to be inspectedjStarting detection time for starting detection;A j representing equipment to be inspectedjArrival time at the detection location;x ijk =1 indicates that the sample is detected in the tableiGo up equipment of waiting to examinejIs the firstkAnd do the detection otherwisex ijk =0；S i Indicating the detection tableiThe number of devices to be detected;T i indicating the starting idle time of the detection platform body i;y ijk is shown on the detection platformiAnd (4) the idle time between the detection of the (K-1) th device to be detected and the detection of the K-th device to be detected is completed.
2. The method of claim 1, wherein said determining a target scheduling policy from said initial set of scheduling policies comprises:
optimizing the initial scheduling strategy set based on the selection operation and the cross operation of the genetic algorithm to obtain an optimized scheduling strategy set;
Performing tabu search on any one of the optimal scheduling strategies in the optimal scheduling strategy set to obtain candidate optimal scheduling strategies corresponding to the any one of the optimal scheduling strategies;
and carrying out replacement operation on any one of the optimal scheduling strategies based on the candidate optimal scheduling strategies to obtain a replaced optimal scheduling strategy set serving as an initial scheduling strategy set.
3. The method according to claim 2, wherein the replacing the any one of the optimal scheduling policies based on the candidate optimal scheduling policy to obtain a replaced optimal scheduling policy set includes:
determining a target optimal scheduling strategy for replacing any optimal scheduling strategy in the candidate optimal scheduling strategies;
and replacing any one of the optimal scheduling strategies by using the target optimal scheduling strategy to obtain a replaced optimal scheduling strategy set.
4. The method of claim 1, wherein an initial scheduling policy in the initial scheduling policy set is used to characterize a start detection time of any device to be detected at any detection platform; the initial scheduling strategy comprises the detection sequence of any one piece of equipment to be detected on any detection platform body; the optimizing the initial scheduling policy set based on the objective function to obtain an optimized scheduling policy set includes:
Aiming at any one of the devices to be detected in each initial scheduling strategy, if the service item of the detection platform body where the any one of the devices to be detected is judged to be in accordance with the item to be detected of the any one of the devices to be detected, calculating the detection sequence included in each initial scheduling strategy, the arrival time of the any one of the devices to be detected, the item detection duration of the any one of the devices to be detected and the starting detection time of the any one of the devices to be detected through the objective function to obtain the fitness value of the each initial scheduling strategy;
and optimizing the initial scheduling strategy set according to the fitness value of each initial scheduling strategy to obtain the optimized scheduling strategy set.
5. The method of claim 4, wherein optimizing the initial scheduling policy set according to the fitness value of each initial scheduling policy to obtain the optimized scheduling policy set comprises:
determining an optimal initial scheduling strategy in the initial scheduling strategy set according to the fitness value of each initial scheduling strategy;
if the iteration times do not reach the preset time threshold, selecting at least part of initial scheduling strategies in the initial scheduling strategy set and the optimal initial scheduling strategy to form a cross scheduling strategy set;
Performing cross operation based on the cross scheduling policy set to obtain a variation scheduling policy which corresponds to any one of the initial scheduling policies in the cross scheduling policy set one by one;
and if the variation scheduling policy meets the detection preset rule, replacing the cross scheduling policy set in the initial scheduling policy set with the variation scheduling policy to obtain the optimized scheduling policy set.
6. The method according to any one of claims 1 to 5, wherein the detection preset rule is used to determine a constraint condition of an objective function; the detection preset rule comprises the following steps:
the detection duration of each device to be detected depends on the item to be detected;
each detection platform body detects one device to be detected at a time;
each device to be detected is detected once in the same detection item;
the to-be-detected items of each to-be-detected device meet the service items provided by the detection platform body.
7. The method according to any one of claims 1 to 5, wherein constructing a detection scheduling model that complies with detection preset rules from the item to be detected comprises:
acquiring detection platform state information and detection site environment information;
and constructing a detection scheduling model which complies with detection preset rules according to the detection platform body state information, the detection place environment information and the items to be detected.
8. A scheduling policy determining apparatus applied to a detection service scheduling management terminal connected to at least one detection station of a detection site, the apparatus comprising:
the management interface providing module is used for providing a detection service scheduling management interface;
the to-be-detected information determining module is used for determining to-be-detected related information of to-be-detected equipment according to the information input operation of the to-be-detected equipment through the detection service scheduling management interface; the to-be-detected related information comprises to-be-detected items of to-be-detected equipment and arrival time of the to-be-detected equipment to the detection place;
the scheduling model construction module is used for constructing a detection scheduling model which complies with detection preset rules according to the item to be detected; the detection preset rule is used for agreeing on a detection relation between the equipment to be detected and the detection platform body; the detection scheduling model is used for generating an initial scheduling strategy set; and an objective function for constructing the detection scheduling model; the parameters of the objective function comprise an arrival time parameter, a detection duration parameter, a starting detection time parameter and a detection sequence parameter; the arrival time parameter is used for describing the arrival time;
The scheduling policy determining module is used for determining a target scheduling policy according to the initial scheduling policy set; wherein, the determining a target scheduling policy according to the initial scheduling policy set includes: optimizing the initial scheduling strategy set based on the objective function to obtain an optimized scheduling strategy set; determining the target scheduling strategy according to the optimized scheduling strategy set;
the objective function representation aims at minimizing the waiting time and the detection time of all the equipment to be detected in the detection place, and the objective function representation adopts any one of the following forms:
wherein ,Fthe function of the object is represented by a function of the object,i=（1,2，……，I）∈Brepresenting a collection of test tables;j=（1,2，……S）∈Vrepresenting a set of devices to be inspected;k=（1,2，……S）∈Urepresenting the detection sequence of the equipment to be detected;C ij representing equipment to be inspectedjIn-detection table bodyiDetecting the required detection time length;m j representing equipment to be inspectedjStarting detection time for starting detection;A j representing equipment to be inspectedjArrival time at the detection location;x ijk =1 indicates that the sample is detected in the tableiGo up equipment of waiting to examinejIs the firstkAnd do the detection otherwisex ijk =0；S i Indicating the detection tableiThe number of devices to be detected;T i indicating the starting idle time of the detection platform body i; y ijk Is shown on the detection platformiAnd (4) the idle time between the detection of the (K-1) th device to be detected and the detection of the K-th device to be detected is completed.
9. The apparatus of claim 8, wherein the scheduling policy determination module is further configured to optimize the initial set of scheduling policies based on a selection operation and a crossover operation of a genetic algorithm to obtain an optimized set of scheduling policies; performing tabu search on any one of the optimal scheduling strategies in the optimal scheduling strategy set to obtain candidate optimal scheduling strategies corresponding to the any one of the optimal scheduling strategies; and carrying out replacement operation on any one of the optimal scheduling strategies based on the candidate optimal scheduling strategies to obtain a replaced optimal scheduling strategy set serving as an initial scheduling strategy set.
10. A detection service scheduling management terminal comprising a memory and a processor, said memory storing a computer program, characterized in that said processor implements the scheduling policy determination method according to any one of claims 1 to 7 when executing said computer program.
11. A detection service scheduling management terminal, characterized in that the terminal comprises:
the man-machine interaction unit is used for providing a detection service scheduling management interface;
The main control unit is connected with the man-machine interaction unit and comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the scheduling policy determining method according to any one of claims 1 to 7 when executing the computer program;
the debugging interface unit is connected with the main control unit and used for connecting at least one detection platform body and/or at least one device to be detected.
12. A computer readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the scheduling policy determination method of any one of claims 1 to 7.
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