CN111062659B - Task execution planning method and device and computer system - Google Patents
Task execution planning method and device and computer system Download PDFInfo
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Abstract
The application discloses a method, a device and a computer system for planning task execution, wherein the method comprises the following steps: calculating the minimum number of task executors required for meeting the task requirement by using a linear programming algorithm according to the predicted task parameters of each block in a preset time period; determining a task execution circuit corresponding to the minimum number of task executors as an initial task execution circuit, wherein the initial task execution circuit consists of the path relation of the blocks; when any initial task execution line does not meet the preset conditions, the variable neighborhood search algorithm is used for adjusting the path relation of the blocks contained in the initial task execution line in real time to obtain a real-time task execution line, the task execution line with the optimal full preset time period is planned before the task execution is started, the initial task execution line is adjusted in real time according to the real-time state of the initial task execution line, and the task execution in the full preset time period can meet the task requirements.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, an apparatus, and a computer system for planning task execution.
Background
With the rapid expansion of the take-away industry, instant logistics has also rapidly developed. In the traditional take-away delivery field, the delivery network is a mesh structure, and a distributor can take parts from a plurality of merchants within a service range and then deliver the parts to users within a preset range of the merchants. However, in the fields of business overload and freshness, a distribution station generally provides services to all users within the coverage of the distribution station, so that the distribution network structure is different from the traditional takeout distribution field and is a structure radiating from a single point to the periphery.
When a user places an order, the instant logistics distribution system in the traditional takeout distribution field traverses all distributors meeting conditions according to the initial position of the order and the end position of the order, comprehensively evaluates the real-time positions of the distributors, the current unfinished task number, order forward conditions and other influencing factors, and distributes the order of the user to the distributor which is considered to be optimal by the system when the order is generated so as to achieve the aims of shortest riding distance, lowest order overtime rate and shortest average distribution time. However, if the order distribution mode is applied to a structure radiating around in a single point in the fields of business overload, freshness and the like, a distributor needs to return for taking goods many times, or all riders are distributing, so that part of orders wait for a long time, the distribution time is delayed, and the use experience of a user is influenced. Meanwhile, the order distribution mode is only a local optimal distribution mode, only the short-term optimal effect of current distribution is considered, and the optimal effect can be achieved when the order distribution in the whole day cannot be achieved.
Disclosure of Invention
In order to solve the defects of the prior art, the main object of the present invention is to provide a method, an apparatus, and a computer system for planning task execution, so as to ensure that an optimal task execution route in a full preset time period is planned on the premise of starting task execution on the premise of minimizing the number of required task executors, and ensure that task execution in the full preset time period can meet task requirements by adjusting the task execution route in real time according to the real-time state of an initial task execution route.
In order to achieve the above object, a first aspect of the present invention provides a method for planning task execution, the method comprising:
calculating the minimum number of task executors required by meeting the task requirements by using a linear programming algorithm according to the predicted task parameters of each block in a preset time period, wherein the task parameters comprise the task requirements and task states of the tasks contained in each block;
determining a task execution circuit corresponding to the minimum number of task executors as an initial task execution circuit, wherein the initial task execution circuit consists of the path relation of the blocks;
and when any initial task execution line does not meet the preset conditions, adjusting the path relation of the blocks contained in the initial task execution line in real time according to the actual task parameters to obtain a real-time task execution line.
In some embodiments, the determining that the task execution route corresponding to the minimum number of task performers is an initial task execution route includes:
and determining that the task execution line corresponding to the minimum number of task executors is an initial task execution line and the execution cycle corresponding to the initial task execution line is a target execution cycle.
In some embodiments, the task state includes a predicted task volume per tile.
In some embodiments, the predicting task parameters of each block within the preset time period, calculating the minimum number of task performers required to meet the task requirements using a linear programming algorithm, the task parameters including the task requirements and task states of the tasks included in each block includes:
calculating possible task execution circuits and execution periods of the task execution circuits by using a linear programming algorithm according to the task state and the task requirements of the tasks contained in each block in the predicted preset time period;
and adjusting the possible task execution lines and the execution period of the task execution lines until the number of task executors required by meeting the task requirements is minimum, and obtaining the minimum number of task executors.
In some embodiments, the preset condition includes a preset threshold of an execution parameter of the initial task execution route, and when any of the initial task execution routes does not satisfy the preset condition, the real-time adjustment of the path relationship of the blocks included in the initial task execution route according to the actual task parameter is performed to obtain the real-time task execution route includes:
when the execution parameter of any initial task execution line exceeds the preset threshold value,
calculating according to actual task parameters by using a variable neighborhood search algorithm to obtain target blocks corresponding to the initial task execution circuit exceeding the preset threshold and the path relation corresponding to each target block after adjustment;
and moving each target block to the initial task execution circuit containing the path relation corresponding to the target block after adjustment, so as to obtain a real-time task execution circuit.
In some embodiments, before calculating the minimum number of task performers required to meet the task requirement using a linear programming algorithm according to the predicted task parameters of each block within the preset time period, the method further comprises:
and predicting according to the task state and the task requirement of the historical task of each block in the preset time period, and obtaining the task state and the task requirement of the task contained in each block in the predicted preset time period.
In some embodiments, after determining that the task execution path corresponding to the minimum number of task performers is an initial task execution path and the execution cycle corresponding to the initial task execution path is a target execution cycle, the method further includes:
and distributing the initial task execution line of each target execution period to the corresponding task performer according to the corresponding relation between the initial task execution line of each target execution period and the task performer.
In a second aspect, the present application provides a device for planning task execution, the device comprising:
the planning module is used for calculating the minimum number of task executors required by meeting the task requirements by using a linear programming algorithm according to the predicted task parameters of each block in a preset time period, wherein the task parameters comprise the task state and the task requirements of the tasks contained in each block;
the processing module is used for determining a task execution line corresponding to the minimum number of task executors as an initial task execution line, and the task execution line is composed of the path relation of the blocks;
and the adjusting module is used for adjusting the path relation of the blocks contained in the initial task execution circuit in real time according to actual task parameters to obtain a real-time task execution circuit when any initial task execution circuit does not meet the preset condition.
In some embodiments, the processing module may be further configured to determine that a task execution line corresponding to the minimum number of task performers is an initial task execution line and an execution cycle corresponding to the initial task execution line is a target execution cycle.
In a third aspect, the present application provides a computer system comprising:
one or more processors; and memory associated with the one or more processors, the memory for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
calculating the minimum number of task executors required by meeting the task requirement by using a linear programming algorithm according to the predicted task parameters of each block in a preset time period, wherein the task parameters comprise the task state and the task requirement of the task contained in each block;
determining a task execution circuit corresponding to the minimum number of task executors as an initial task execution circuit, wherein the initial task execution circuit consists of the path relation of the blocks;
and when any initial task execution line does not meet the preset condition, adjusting the path relation of the blocks contained in the initial task execution line in real time according to the actual task parameters to obtain a real-time task execution line.
According to the specific embodiments provided herein, the present application discloses the following technical effects:
the application discloses that according to the task parameters of each block in a predicted preset time period, the task parameters comprise the task state and the task requirements of the tasks of each block, the minimum number of task executors required for meeting the task requirements is calculated by using a linear programming algorithm, and the cost of using or hiring the task executors is reduced on the premise of ensuring that the task requirements are met; further, the application also provides a method for determining the task execution line corresponding to the minimum number of task executors as an initial task execution line, when any initial task execution line does not meet the preset conditions, real-time adjustment is performed on the connection relation of the blocks included in the initial task execution line according to actual task parameters to obtain a real-time task execution line, so that the task execution line with the optimal full preset time period is planned on the premise of ensuring the minimum number of required task executors, and is adjusted in real time according to the real-time state of the initial task execution line, and the task execution in the full preset time period can meet the task requirements;
furthermore, the method and the device also provide that the task state and the task requirement of each block in the preset time period are predicted according to the task state and the task requirement of the historical task of each block in the preset time period, so that the task state and the task requirement of each block in the preset time period are predicted in advance, and the efficiency is improved for initial circuit planning;
the application also provides that the blocks contained in the initial task execution circuit of each target execution period are distributed to the corresponding task performers according to the corresponding relation between the initial task execution circuit of each target execution period and the task performers; each task executor only needs to process the task execution circuit of the target execution cycle distributed by the task executor, and does not need to turn back for multiple times, so that the execution efficiency of executing tasks is improved.
It is not necessary for any product to achieve all of the above-described technical effects simultaneously in the practice of the present application.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of delivery cycles provided by an embodiment of the present application;
FIG. 2 is a schematic diagram of an initial distribution route provided by an embodiment of the present application;
FIG. 3 is a schematic diagram of a real-time distribution line provided by an embodiment of the present application;
FIG. 4 is a flow chart of a method provided by an embodiment of the present application;
FIG. 5 is a block diagram of an apparatus according to an embodiment of the present disclosure;
fig. 6 is a computer system structure diagram provided in the embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As described in the background art, distribution network structures such as Shanghai, Shengxian and the like are distributed in a single-point and all-around radiation manner, an order dispatching method used in the traditional takeout distribution field cannot be used, the order dispatching method used in the traditional takeout distribution field is only a locally optimal distribution mode, only the optimal effect of current distribution is considered, and the distribution pressure is not considered to be reserved for future orders.
In order to solve the technical problems, the application provides a predicted task state and task requirements of each block in a preset time period, and a linear programming algorithm is used for calculating the minimum number of task executors required by meeting the task requirements; according to the minimum task performer number, determining a task performing line corresponding to the minimum task performer number as an initial task performing line; when any initial task execution route does not meet the preset condition, the variable neighborhood search algorithm is used for adjusting the path relation of the blocks contained in the initial task execution route in real time to obtain the real-time task execution route, and the task execution route which is optimal in the full preset time period is planned before the task execution is started.
Furthermore, the method and the system further provide that the blocks contained in the initial task execution line of each target execution cycle are distributed to the corresponding task performers according to the corresponding relation between the initial task execution line of each target execution cycle and the task performers, each distributor only needs to complete the order on the distributed task execution line, multiple turning-back is not needed, the distributor returns to the distribution station to take the order to be distributed, the distributor waits for the order at any time in the distribution station, the time required by distribution is saved, and the distribution efficiency is improved.
Example one
To achieve the above object, taking the example of the delivery of the goods from the delivery station to the user by the rider, the above method can be implemented by the following steps:
dividing the office shift of a rider according to the historical ordering time trend of each day order and the service time of a distribution station;
for example, the distribution service time of the distribution station is 08:00-00:00, and the daily distribution peak time is 10:00-11:00 and 16:00-20: 00. The rider's working time can be divided into three shifts: the early shift is 08:00-12:00 and 16:00-20:00, the normal shift is 10:00-19:00, and the night shift is 15:00-00:00, so that the number of riders in each time interval can meet the distribution requirement in the time interval.
Step two, predicting the order state and the distribution demand in the distribution station distribution range of the next day;
the method comprises the steps of firstly, collecting historical order information and promotion information of a distribution station within a distribution range of the distribution station, wherein the historical order information comprises order generation time, distribution time, delivery duration, customer addresses and the like, and the promotion information comprises promotion activity level, coupon sending amount and the like.
And predicting the order state and the distribution demand in the distribution range of the next day distribution station according to the historical order information and the promotion information of the distribution station by using a prediction method such as a time sequence model, a neural network model, a random forest model and the like.
Then, according to the position range of the independent blocks in the distribution area radiated by the distribution station or the business circles, the predicted order is divided to obtain the position range of each block in each time period t 0 Predicted order status and delivery requirements within.
The predicted order state includes factors such as predicted order quantity, predicted riding speed of a rider, position of a delivery station and position of an order.
The predicted delivery demand includes a predicted order delivery time limit, and the delivery time limit is delivery time promised to the user when the order is placed.
Step three, according to each block predicted in each time period t 0 Calculating the minimum number of riders by using a linear programming algorithm according to the order state and the distribution demand in the system;
the distribution lines are a distribution area set formed by a plurality of blocks in a distribution range of the distribution stations in series from the distribution stations, one distribution line is distributed by one rider within one distribution wave, and the distribution sequence of each distribution of the rider is not completely the same.
The delivery times consist of the order pressing time length and the delivery time length. The order pressing time duration refers to the time duration from the time when the previous rider leaves the distribution station to the time when the next rider reaches the order receiving upper limit and leaves the distribution station to start distribution; the delivery time period refers to a period from when the rider leaves the delivery station to start delivery to when the rider finishes delivery to return to the delivery station. Wherein, the above time period t 0 Is the minimum time unit of the distribution frequency, and the single pressing time length and the distribution time length can be t 0 Is expressed by a multiple of (e.g. 2 t) the time of pressing the bill 0 Delivery time period 5t 0 Delivery times of 7t 0 。
As shown in FIG. 1, T 10 Is the time of first order creation, T 11 For the time, T, when the rider A leaves the dispensing station to start dispensing 12 The time when the delivery for the rider A is finished and the delivery station is returned, wherein the duration of the pressing of the 1 st delivery wave rider A is t 1 ＝T 11 -T 10 The delivery duration of the rider a is the duration of the TSP problem relating to the order amount within the predicted order duration, the rider riding speed, the order delivery duration, the order delivery age, the delivery station position, and the order position, and the like, and may be expressed as TSP (t) 1 )＝T 12 -T 11 In order to meet the requirements of users, the original distribution lines and the original distribution frequency should be planned to meet the requirements of order distribution timeliness, that is, the distribution duration should meet the following conditions:
TSP(x 1 )≤TS 1
TSP(x 2 ,x 1 )≤TS 2
TSP(x 3 ,x 1 x 2 )≤TS 3
……
TSP(x i ,x 1 x 2 ……x i-1 )
wherein x is i Represents t 1 The ith order in time, TSP (x) i ,x 1 x 2 ……x i-1 ) Indicating the delivery duration, TS, of the ith order i Indicating the delivery age of the ith order.
The above formula means the time t of the rider A pressing the order 1 All orders within cannot exceed the delivery age of the order itself.
By analogy, the order pressing time of the ith distribution order is t i ＝T i1 -T i0 The delivery time is TSP (t) i )＝T i2 -T i1 In order to facilitate planning of distribution lines, the order pressing duration of each distribution line in each distribution wave is simplified to be t ═ t 1 ＝t 2 ……＝t i The distribution time of the route is TSP (t) max (TSP (t) 1 ),TSP(t 2 ),……,TSP(t i ) Represents the delivery time period of the whole line by the longest one of the delivery time periods of one line.
In order to realize the predicted distribution demand, it is necessary to ensure that the rider does not need to return to the distribution station to take the goods in the distribution way, therefore, at least one rider is waiting for the order in the distribution station, and the number of riders required by one distribution line is
Represent
The value of (b) is an integer.
In order to reduce the distribution cost of the distribution station, the number of riders needs to be minimized on the premise of meeting the distribution requirement of the order, and the method is based on
The number of riders required for a distribution line is positively correlated with the order pressing time and the distribution time of the line. Thus, using a linear programming algorithm, with a minimum number of riders as the objective function of the linear programming, can be expressed as:
the constraint of the objective function is:
wherein n is j The number of riders of the jth line is represented, P represents the number of all blocks, and m represents the number of distribution lines;
Due to each predicted time period t 0 The order state of each block in the distribution line comprises related time parameters such as the number of orders, the riding speed of a rider and the time length required by order distribution delivery, so that the order pressing time length and the distribution time length of the distribution line can be calculated according to the order state of the blocks in the distribution line, and the time periods t included in one distribution wave can be determined according to the order pressing time length and the distribution time length 0 。
According to the objective function and the constraint condition of the linear programming, using a linear programming algorithm and according to each predicted time period t 0 And calculating a solution of a possible distribution line and distribution wave number according to the order state of each block in the system, and continuously adjusting the order pressing time length and the distribution time length by adjusting the solution until the minimum rider number given by a linear programming algorithm is obtained, wherein the distribution line corresponding to the minimum rider number is an initial distribution line, and the distribution wave number corresponding to the initial distribution line is a target distribution wave number. When the minimum number of riders is determined, the serial point of each distribution line and the number of riders required for each line are also determined.
Determining a distribution route corresponding to the minimum number of riders as an initial distribution route, wherein the distribution wave frequency corresponding to the initial distribution route is a target distribution wave frequency;
fifthly, distributing the distribution line of each target distribution wave number to the corresponding rider according to the corresponding relation between the distribution line of each initial distribution wave number and the rider;
the rider can wait at the distribution station when the distributed target distribution wave number arrives, when the distributed order of the block contained in the distribution line meets the preset condition, the rider starts to distribute from the distribution station, at least one rider is ensured to wait for the order at the distribution station at any time, and the rider does not need to return to the distribution station to take the order which does not belong to the distribution wave number of the rider, so that the distribution efficiency is improved.
Step five, according to the actual ordering situation of the user, dynamically adjusting the distribution line with the actual order state exceeding the preset threshold value by using a variable neighborhood search algorithm to obtain a real-time distribution line;
the preset threshold includes: the order number of the distribution line is not higher than the preset number, the single order quantity of the rider is not higher than the preset order quantity upper limit, the actual time length of the rider for completing distribution wave times is not longer than the preset time length of the distribution wave times, and the actual order distribution time length of the rider exceeds the distribution time efficiency.
The process of dynamic adjustment by using the variable neighborhood search algorithm comprises the following steps:
A. defining an optimization objective function as distributing orders x _ i within the time t of the order pressing to m riders, so that the total riding distance of all the riders is shortest;
B. defining inter-group optimization neighborhoods swap and cross and intra-group optimization neighborhoods two-opt;
C. the constraint conditions are defined as:
(1) the number of the riders is m, and each rider distributes the goods once;
(2) delivery time per order TSP (x) i ,x 1 x 2 ……x i-1 ) Delivery timeliness TS to be earlier than order i
(3) The single delivery unit quantity of each rider does not exceed the upper limit M of the loading unit quantity
(4) Actual time length of each rider for completing distribution wave time does not exceed distribution time length TSP (t)
D. Generating an initial solution s0 for order reassignment using the BestInsert algorithm;
E. define local neighborhood search descent (VND) flow:
performing swap search on any two rider order groups based on s0 until s1 is searched to be superior to s0, otherwise s1 is s 0;
performing cross search on any two rider order groups based on s1 until s2 is searched to be better than s1, otherwise s2 is s 1;
performing a two-opt group order sequence optimization for each rider at s 1;
F. defining a shaking process:
randomly draw 40% of orders for all riders at s 0;
inserting the extracted order into the existing rider according to a BestInsert algorithm to generate a new order redistribution solution;
G. and obtaining an optimal order redistribution solution by using a BestInsert algorithm, wherein the solution comprises all orders to be redistributed, the distribution line to which the orders originally belong and the distribution line to which the orders belong after adjustment.
The above reallocation process can also be implemented using other variable neighborhood search algorithms than the bestsert algorithm.
Fig. 2 shows an initial distribution route diagram, when the order status of the b1-b5 route exceeds a preset threshold, the b1-b5 route is adjusted by using the above-mentioned neighborhood search algorithm, and then the block to which all orders to be redistributed belong is found to be b5, as shown in fig. 3, the block b5 to which all orders belong is adjusted to the a1-a3 route, so that dynamic adjustment of the distribution route is realized, real-time distribution routes are obtained, and it is ensured that the actual distribution volume of each distribution route does not exceed the distribution capacity.
Example two
Corresponding to the above embodiments, the present application provides a method for planning task execution, as shown in fig. 4, the method includes:
410. calculating the minimum number of task executors required by meeting the task requirements by using a linear programming algorithm according to the predicted task parameters of each block in a preset time period, wherein the task parameters comprise the task requirements and task states of the tasks contained in each block;
preferably, the task state includes a predicted task amount per tile.
Preferably, the step of calculating the minimum number of task performers required to meet the task requirement by using a linear programming algorithm according to the predicted task parameter of each block within the preset time period includes:
411. calculating possible task execution circuits and execution cycles of the task execution circuits by using a linear programming algorithm according to the predicted task state and task requirements of tasks contained in each block within a preset time period;
and adjusting the possible task execution lines and the execution period of the task execution lines until the number of task executors required by meeting the task requirements is minimum, and obtaining the minimum number of task executors.
Before calculating the minimum number of task executors required for meeting the task requirement by using a linear programming algorithm according to the predicted task parameters of each block in the preset time period, the method further comprises the following steps:
412. and predicting according to the task state and the task requirement of the historical task of each block in the preset time period, and obtaining the task state and the task requirement of the task contained in each block in the predicted preset time period.
420. According to the minimum task performer number, determining a task performing circuit corresponding to the minimum task performer number as an initial task performing circuit, wherein the initial task performing circuit comprises a path relation of the block;
preferably, the path relation is a task execution path trajectory which starts from a start point of task execution, connects all blocks included in the path relation, and finally returns to the start point of task execution.
Preferably, the determining, according to the minimum number of task performers, that the task performance route corresponding to the minimum number of task performers is an initial task performance route includes:
421. and determining that the task execution line corresponding to the minimum task performer number is an initial task execution line and the execution cycle corresponding to the initial task execution line is a target execution cycle according to the minimum task performer number.
Preferably, after determining that the task execution route corresponding to the minimum number of task performers is an initial task execution route and that the execution cycle corresponding to the initial task execution route is a target execution cycle, the method further includes:
422. and distributing the initial task execution line of each target execution period to the corresponding task performer according to the corresponding relation between the initial task execution line of each target execution period and the task performer.
430. And when any initial task execution line does not meet the preset condition, adjusting the path relation of the blocks contained in the initial task execution line in real time according to the actual task parameters to obtain a real-time task execution line.
Preferably, the preset condition includes a preset threshold of an execution parameter of the initial task execution route, and when any of the initial task execution routes does not satisfy the preset condition, the method for obtaining a real-time task execution route includes the steps of using a variable neighborhood search algorithm to adjust a path relationship of the blocks included in the initial task execution route in real time:
431. when the execution parameter of any initial task execution line exceeds a preset threshold value,
obtaining a target block of the initial task execution circuit exceeding the preset threshold value and a target initial task execution circuit of the target block by using a variable neighborhood search algorithm;
and moving the target block to the connection relation included in the target initial task execution line to obtain a real-time task execution line.
EXAMPLE III
Corresponding to the above method, the present application provides a task execution planning apparatus, as shown in fig. 5, the apparatus includes:
a planning module 510, configured to calculate, according to a predicted task parameter of each block in a preset time period, a minimum number of task performers required to meet the task requirement by using a linear programming algorithm, where the task parameter includes a task state and a task requirement of a task included in each block;
a processing module 520, configured to determine, according to the minimum number of task performers, that a task performance path corresponding to the minimum number of task performers is an initial task performance path, where the initial task performance path is formed by a path relationship of the block;
an adjusting module 530, configured to, when any of the initial task execution routes does not meet a preset condition, perform real-time adjustment on a path relationship of the block included in the initial task execution route according to an actual task parameter, so as to obtain a real-time task execution route.
Preferably, the processing module 520 is further configured to determine, according to the minimum number of task performers, that a task performance line corresponding to the minimum number of task performers is an initial task performance line and that a performance cycle corresponding to the initial task performance line is a target performance cycle.
Preferably, the planning module 510 is further configured to calculate the minimum number of task performers required to meet the task requirement by using a linear programming algorithm according to a predicted task parameter of each block within a preset time period, where the task parameter includes a task state and a task requirement of a task included in each block, and the task state includes a predicted task amount of each block.
Preferably, the planning module 510 is further configured to calculate a possible task execution route and an execution cycle of the task execution route by using a linear programming algorithm according to the predicted task state and task requirement of the task included in each block within the preset time period;
and adjusting the possible task execution routes and the execution periods of the task execution routes until the number of task executors required by meeting the task requirements is minimum, and obtaining the minimum number of task executors.
Preferably, the preset condition includes a preset threshold of the execution parameter of the initial task execution path, and the adjusting module 530 is further configured to, when the execution parameter of any of the initial task execution paths exceeds the preset threshold,
obtaining a target block of the initial task execution circuit exceeding the preset threshold value and a target initial task execution circuit of the target block by using a variable neighborhood search algorithm;
and moving the target block to the connection relation included in the target initial task execution line to obtain a real-time task execution line.
Preferably, the planning apparatus further includes a predicting module 540, configured to predict the task state and the task requirement of the historical task of each block in the preset time period, and obtain the predicted task state and task requirement of the task included in each block in the preset time period.
Preferably, the processing module 520 is further configured to allocate the initial task execution route of each target execution cycle to a corresponding task executor according to a corresponding relationship between the initial task execution route of each target execution cycle and the task executor.
Example four
Corresponding to the above embodiments, the present application further provides a computer system comprising one or more processors; and memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
fig. 6 illustrates an architecture of a computer system, which may include, in particular, a processor 1510, a video display adapter 1511, a disk drive 1512, an input/output interface 1513, a network interface 1514, and a memory 1520. The processor 1510, the video display adapter 1511, the disk drive 1512, the input/output interface 1513, the network interface 1514, and the memory 1520 may be communicatively connected by a communication bus 1530.
The processor 1510 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solution provided by the present Application.
The Memory 1520 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, or the like. The memory 1520 may store an operating system 1521 for controlling the operation of the computer system 1500, a Basic Input Output System (BIOS) for controlling low-level operations of the computer system 1500. In addition, a web browser 1523, a data storage management system 1524, an icon font processing system 1525, and the like may also be stored. The icon font processing system 1525 can be an application program that implements the operations of the foregoing steps in this embodiment. In summary, when the technical solution provided in the present application is implemented by software or firmware, the relevant program code is stored in the memory 1520 and called for execution by the processor 1510.
The input/output interface 1513 is used for connecting an input/output module to realize information input and output. The i/o module may be configured as a component within the device (not shown) or may be external to the device to provide corresponding functionality. Wherein the input devices may include a keyboard, mouse, touch screen, microphone, various sensors, etc., and the output devices may include a display, speaker, vibrator, indicator light, etc.
The network interface 1514 is used to connect a communication module (not shown) to enable the communication interaction of the present device with other devices. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).
The bus 1530 includes a path to transfer information between the various components of the device, such as the processor 1510, the video display adapter 1511, the disk drive 1512, the input/output interface 1513, the network interface 1514, and the memory 1520.
In addition, the computer system 1500 may also obtain information of specific extraction conditions from the virtual resource object extraction condition information database 1541 for performing condition judgment, and the like.
It should be noted that although the above devices only show the processor 1510, the video display adapter 1511, the disk drive 1512, the input/output interface 1513, the network interface 1514, the memory 1520, the bus 1530, etc., in a specific implementation, the devices may also include other components necessary for proper operation. Furthermore, it will be understood by those skilled in the art that the apparatus described above may also include only the components necessary to implement the solution of the present application, and not necessarily all of the components shown in the figures.
From the above description of the embodiments, it is clear to those skilled in the art that the present application can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present application or portions thereof that contribute to the prior art may be embodied in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, or the like, and includes several instructions for enabling a computer device (which may be a personal computer, a cloud server, or a network device) to execute the method according to the embodiments or some portions of the embodiments of the present application.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments, which are substantially similar to the method embodiments, are described in a relatively simple manner, and reference may be made to some descriptions of the method embodiments for relevant points. The above-described system and system embodiments are only illustrative, wherein the units described as separate parts may or may not be physically separate, and the parts displayed 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 modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement without inventive effort.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (7)
1. A method of planning task execution, the method comprising:
calculating the minimum number of task executors required for meeting the task requirements by using a linear programming algorithm according to the predicted task parameters of each block in a preset time period, wherein the task parameters comprise the task requirements and the task states of the tasks contained in each block;
determining that the task execution circuit corresponding to the minimum number of task executors is an initial task execution circuit and an execution cycle corresponding to the initial task execution circuit is a target execution cycle, wherein the initial task execution circuit consists of the path relation of the blocks;
when any initial task execution line does not meet a preset condition, adjusting the path relation of the blocks contained in the initial task execution line in real time according to actual task parameters to obtain a real-time task execution line;
after determining that the task execution path corresponding to the minimum number of task performers is an initial task execution path and the execution cycle corresponding to the initial task execution path is a target execution cycle, the method further includes:
and distributing the initial task execution line of each target execution period to the corresponding task performer according to the corresponding relation between the initial task execution line of each target execution period and the task performer.
2. The method of claim 1, wherein the task state comprises a predicted task volume per block.
3. The method of claim 1, wherein the step of calculating the minimum number of task performers required to meet the task requirements for each block within the predicted preset time period using a linear programming algorithm comprises:
calculating possible task execution circuits and execution cycles of the task execution circuits by using a linear programming algorithm according to the predicted task state and task requirements of tasks contained in each block within a preset time period;
and adjusting the possible task execution lines and the execution period of the task execution lines until the number of task executors required by meeting the task requirements is minimum, and obtaining the minimum number of task executors.
4. The method according to claim 3, wherein the preset condition includes a preset threshold of an execution parameter of the initial task execution path, and the obtaining a real-time task execution path by adjusting the path relationship of the block included in the initial task execution path in real time according to an actual task parameter comprises:
when the execution parameter of any initial task execution line exceeds the preset threshold value,
calculating according to actual task parameters by using a variable neighborhood search algorithm to obtain target blocks corresponding to the initial task execution circuit exceeding the preset threshold and the path relation corresponding to each target block after adjustment;
and moving each target block to the initial task execution circuit containing the path relation corresponding to the target block after adjustment to obtain a real-time task execution circuit.
5. The method of claim 1, wherein before calculating the minimum number of task performers required to meet the task requirements using a linear programming algorithm based on the predicted task parameters for each block over the predetermined time period, the method further comprises:
and predicting according to the task state and the task requirement of the historical task of each block in the preset time period, and obtaining the task state and the task requirement of the task contained in each block in the predicted preset time period.
6. An apparatus for planning task execution, the apparatus comprising:
the planning module is used for calculating the minimum number of task executors required by meeting the task requirements by using a linear programming algorithm according to the predicted task parameters of each block in a preset time period, wherein the task parameters comprise the task state and the task requirements of the tasks contained in each block;
the processing module is used for determining that the task execution circuit corresponding to the minimum number of task executors is an initial task execution circuit and the execution cycle corresponding to the initial task execution circuit is a target execution cycle, wherein the initial task execution circuit consists of the path relation of the blocks;
the adjusting module is used for adjusting the path relation of the blocks contained in the initial task execution circuit in real time according to actual task parameters to obtain a real-time task execution circuit when any initial task execution circuit does not meet preset conditions;
the processing module is further configured to allocate the initial task execution route of each target execution cycle to a corresponding task executor according to a corresponding relationship between the initial task execution route of each target execution cycle and the task executor after determining that the task execution route corresponding to the minimum number of task executors is an initial task execution route and the execution cycle corresponding to the initial task execution route is a target execution cycle.
7. A computer system, the system comprising:
one or more processors; and memory associated with the one or more processors for storing program instructions that, when read and executed by the one or more processors, perform operations comprising:
calculating the minimum number of task executors required by meeting the task requirement by using a linear programming algorithm according to the predicted task parameters of each block in a preset time period, wherein the task parameters comprise the task state and the task requirement of the task contained in each block;
determining that the task execution circuit corresponding to the minimum number of task executors is an initial task execution circuit and an execution cycle corresponding to the initial task execution circuit is a target execution cycle, wherein the initial task execution circuit consists of the path relation of the blocks;
when any initial task execution line does not meet a preset condition, adjusting the path relation of the blocks contained in the initial task execution line in real time according to actual task parameters to obtain a real-time task execution line;
after determining that the task execution route corresponding to the minimum number of task performers is an initial task execution route and the execution cycle corresponding to the initial task execution route is a target execution cycle, allocating the initial task execution route of each target execution cycle to the corresponding task performer according to the corresponding relationship between the initial task execution route of each target execution cycle and the task performer.
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| CN109978213A (en) * | 2017-12-28 | 2019-07-05 | 北京京东尚科信息技术有限公司 | A kind of task path planning method and device |
| CN110443541A (en) * | 2019-07-01 | 2019-11-12 | 北京三快在线科技有限公司 | A kind of pressure form processing method and device |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109978213A (en) * | 2017-12-28 | 2019-07-05 | 北京京东尚科信息技术有限公司 | A kind of task path planning method and device |
| CN110443541A (en) * | 2019-07-01 | 2019-11-12 | 北京三快在线科技有限公司 | A kind of pressure form processing method and device |
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