CN114580728A - Elevator dispatching method and device, storage medium and electronic equipment - Google Patents
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Abstract
The disclosure relates to the field of logistics storage, in particular to a method and a device for scheduling a hoist, a storage medium and electronic equipment. The elevator dispatching method comprises the following steps: selecting a preset number of tasks as tasks to be planned based on the priority of the tasks to be executed by the elevator; wherein the elevator is provided with a plurality of loading stations; acquiring an initial position of the hoister and a starting point and an end point corresponding to each task to be planned respectively; defining a state function and an operation cost function of the elevator according to a loading station of the elevator, so as to obtain a state transfer equation according to the state function and the operation cost function; and carrying out iterative updating according to the state transition equation based on the initial position and the starting point and the end point to obtain the running path of the hoister. The elevator dispatching method can improve the optimization efficiency of the dispatching path of the elevator with multiple loading stations.
Description
Technical Field
The disclosure relates to the field of logistics storage, in particular to a method for scheduling an elevator, a device for scheduling the elevator, a storage medium and electronic equipment.
Background
The hoister (Well lifting Conveyor/Elevator) is a large mechanical device for transporting by changing potential energy, is usually used as a cargo conveying device in a multi-shuttle system, can load a platform for lifting a cargo carrying box or a semi-closed platform on a vertical upper channel and a vertical lower channel, and carries out the operation of picking and placing the cargo at different positions to realize the operation of loading and unloading the cargo carrying box into and out of a warehouse.
In a general elevator dispatching method, the number of available work stations is taken as an upper limit, and a nearby task is searched and executed. The method for selecting tasks through the principle of proximity only realizes local optimization of task scheduling of the elevator, and is difficult to realize global optimization. In addition, with the increase of the number of available stations of the elevator, the elevator runs empty due to the lack of accurate path planning required among a plurality of tasks executed simultaneously, and the efficiency of the elevator and the utilization rate of multiple layers of stations are reduced.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The invention aims to provide a method, a device, a storage medium and electronic equipment for dispatching a hoist, and aims to improve the efficiency of optimizing dispatching paths of the hoist with multiple loading stations.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to an aspect of the embodiments of the present disclosure, a method for scheduling a hoist is provided, including: selecting a preset number of tasks as tasks to be planned based on the priority of the tasks to be executed by the elevator; wherein the elevator is provided with a plurality of loading stations; acquiring an initial position of the hoister and a starting point and an end point corresponding to each task to be planned respectively; defining a state function and an operation cost function of the elevator according to a loading station of the elevator, so as to obtain a state transfer equation according to the state function and the operation cost function; and carrying out iterative updating according to the state transition equation based on the initial position and the starting point and the end point to obtain the running path of the hoister.
According to some embodiments of the present disclosure, based on the foregoing scheme, the selecting a preset number of tasks as tasks to be planned based on priorities of tasks to be executed by the hoist includes: performing priority gradient sequencing on the tasks to obtain tasks corresponding to the priorities respectively; and selecting a preset number of tasks from the tasks corresponding to the priorities in sequence from high to low according to the priorities as tasks to be planned.
According to some embodiments of the present disclosure, based on the foregoing scheme, the prioritizing the tasks includes: determining tasks corresponding to the first priority based on the service levels of the tasks; determining tasks corresponding to a second priority according to container positions corresponding to tasks except the tasks corresponding to the first priority; calculating the waiting time of each task except the tasks corresponding to the first priority and the second priority so as to determine the task corresponding to a third priority; and determining the task with the undetermined priority as the task corresponding to the fourth priority.
According to some embodiments of the present disclosure, based on the foregoing scheme, the selecting a preset number of tasks from the tasks corresponding to the priorities in sequence from high to low as the tasks to be planned includes: initializing a task set to be selected and a selected task set, and configuring the initial value of the number of the tasks to be selected as the preset number; determining a target priority according to the priorities of tasks in the task set to be selected from high to low; when the number of the tasks corresponding to the target priority is smaller than the number of the tasks to be selected, all the tasks corresponding to the target priority are selected; or when the number of the tasks corresponding to the target priority is larger than the number of the tasks to be selected, selecting the tasks matched with the number of the tasks to be selected from the tasks corresponding to the target priority; updating the task set to be selected, the selected task set and the number of the tasks to be selected based on the selected tasks; and repeating the steps of determining the target priority, selecting the tasks and updating until the number of the tasks to be selected is zero, and taking the tasks in the selected task set as the tasks to be planned.
According to some embodiments of the present disclosure, based on the foregoing scheme, selecting a task whose number matches the number of tasks to be selected from the tasks corresponding to the target priority includes: when non-grouped tasks exist in the selected task set, calculating the similarity between the non-grouped tasks and the tasks corresponding to the target priority, and selecting tasks matched with the number of tasks to be selected according to the similarity; or when non-grouped tasks do not exist in the selected task set, selecting one task from the tasks corresponding to the target priority according to the current position information of the hoister, and calculating the similarity between the selected task and all the tasks corresponding to the target priority except the selected task, so as to select the tasks matched with the number of the tasks to be selected according to the similarity.
According to some embodiments of the disclosure, based on the foregoing scheme, after initializing the candidate task set and the selected task set and configuring the initial value of the number of the candidate tasks to be the preset number when there is a task in execution for the elevator, the method further includes: adding the executing task to the selected task set; and updating the number of the tasks to be selected according to the number of the executed tasks.
According to some embodiments of the present disclosure, based on the foregoing solution, the defining a state function of the hoist according to the loading station of the hoist includes: defining the state function as follows according to the position of the elevator, the carrying station, the tasks to be planned, the execution state of each task to be planned and the carrying station of each task to be planned:
Sk＝[(p,f,i),(t1,f1,t2,f2,...,tN,fN)]；
wherein p is the position of the hoister; f is a loading station of the elevator; i is the ith task to be planned; t is tiThe method comprises the steps of obtaining an execution state of an ith task to be planned, wherein the execution state comprises execution completion, execution in the middle and non-execution; f. ofiAnd N is the total number of tasks to be planned.
According to some embodiments of the present disclosure, based on the foregoing solution, the defining an operation cost function of the hoist according to the loading station of the hoist includes: calculating the running cost of the elevator according to the running distance between two states of the elevator and the running distance of the used loading station to define the running cost function as follows:
C(Sk,Sk+1)＝xpp′×(dpp′+α×lpp′×dpp′)；
wherein, C (S)k,Sk+1) For elevator from state SkTo state Sk+1The running cost of (c); p and p' are respectively the states S of the elevatorkTo state Sk+1The starting point and the end point of the operation; x is the number ofpp′A variable of 0-1 indicating whether a path exists between p and p'; d is a radical ofpp′The running distance of the elevator from p to p'; lpp′The number of used loading stations in the process of moving the elevator from p to p'; and alpha is a weight coefficient. According to some embodiments of the present disclosure, based on the foregoing scheme, the state transition equation is:
C(Sk)＝min{C(Sk,Sk+1)+C(Sk+1)}；
wherein, C (S)k) For the elevator in state SkThe cost of operation; c (S)k,Sk+1) For elevator from state SkTo state Sk+1The running cost of (c); c (S)k+1) For the elevator in state Sk+1The running cost of the time.
According to a second aspect of the embodiments of the present disclosure, there is provided a hoisting machine scheduling device, including: the selection module is used for selecting a preset number of tasks as tasks to be planned based on the priority of the tasks to be executed by the hoister; wherein the elevator is provided with a plurality of loading stations; the acquisition module is used for acquiring the initial position of the hoister and the starting point and the end point corresponding to each task to be planned; the modeling module is used for defining a state function and an operation cost function of the hoister according to a loading station of the hoister so as to obtain a state transfer equation according to the state function and the operation cost function; and the solving module is used for carrying out iterative updating according to the state transition equation based on the initial position and the starting point and the end point to obtain the driving path of the hoister.
According to a third aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium, on which a computer program is stored, the program, when executed by a processor, implementing the elevator dispatching method as in the above embodiments.
According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic apparatus, including: one or more processors; a storage device for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the elevator dispatching method as in the above embodiments.
Exemplary embodiments of the present disclosure may have some or all of the following benefits:
in the technical scheme provided by some embodiments of the disclosure, firstly, a part of tasks are selected according to the priority of the tasks to be executed in the current production environment for scheduling and planning of the elevator, then, a state function is established by using a dynamic planning method to obtain a state transition equation, iterative solution is performed by optimizing the operation cost of the elevator, and finally, the running path of the elevator is obtained to complete scheduling and planning. According to the elevator scheduling method, on one hand, the task execution sequence can be adjusted according to the requirements of the current production environment, and the tasks with high priority can be preferentially executed, so that the elevator execution tasks are adaptive to the current production requirements, and the benefits are maximized; on the other hand, a solving method is provided for planning the operation path of the elevator with a plurality of loading stations, the global optimization of the operation path of the elevator within a certain task quantity can be realized, the utilization rate of the loading stations of the elevator is improved, the dead time of the elevator is reduced, and the operation cost is saved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty. In the drawings:
fig. 1 is a schematic flow chart illustrating a method for dispatching a hoist according to an exemplary embodiment of the disclosure;
FIG. 2 schematically illustrates a flow diagram of a method of prioritization in an exemplary embodiment of the present disclosure;
FIG. 3 is a flow chart diagram schematically illustrating a method for selecting a task to be planned in an exemplary embodiment of the present disclosure;
fig. 4 is a flow chart schematically illustrating a method for scheduling hoists in an exemplary embodiment of the present disclosure;
fig. 5 schematically illustrates a composition diagram of an elevator dispatching device in an exemplary embodiment of the disclosure;
FIG. 6 schematically illustrates a schematic diagram of a computer-readable storage medium in an exemplary embodiment of the disclosure;
fig. 7 schematically shows a structural diagram of a computer system of an electronic device in an exemplary embodiment of the disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the disclosure.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
In the conventional technology, when the task scheduling of the elevator is performed, the task execution near the elevator is often searched according to the principle of proximity, with the upper limit of the available loading stations of the elevator. Along with the increase of the number of layers of the elevator, the logic complexity is increased, the task scheduling difficulty is increased, and due to the lack of accurate path planning required among a plurality of tasks executed simultaneously, the elevator is usually caused to run empty, so that the efficiency of the elevator and the utilization rate of multilayer stations are reduced.
Therefore, the elevator scheduling method can achieve global optimal path of the elevator in a certain task quantity, reduce the no-load of the elevator and improve the utilization rate of multilayer stations.
It should be noted that the present disclosure is primarily directed to a hoist having multiple loading stations, that is, the hoist can simultaneously carry multiple containers to move during operation. The single-loading-station hoister only can carry one container in the operation process, so that the running path of the hoister can be directly obtained after the task execution sequence is determined, and the scheduling optimization problem of the single-loading-station hoister is mostly concentrated in the planning of the task execution sequence. In order to reduce the optimization of the warehouse entry and exit efficiency, the form path planning of the elevator during the execution of a plurality of tasks can be realized, so that the tasks can be completed by using shorter distance and time.
In a warehousing system using a hoist as main transportation equipment, goods are usually stored in containers, the containers are placed in an automatic stereoscopic warehouse, and when the goods are delivered to and stored in the warehouse, the hoist passes through a roadway between shelves, so that the goods taking and placing work is automatically completed.
Implementation details of the technical solution of the embodiments of the present disclosure are set forth in detail below.
Fig. 1 schematically illustrates a flow chart of a method for scheduling hoists in an exemplary embodiment of the present disclosure. As shown in fig. 1, the elevator dispatching method includes steps S101 to S104:
s101, selecting a preset number of tasks as tasks to be planned based on the priority of the tasks to be executed by the elevator; wherein the elevator is provided with a plurality of loading stations;
step S102, acquiring an initial position of the hoister and a starting point and an end point corresponding to each task to be planned respectively;
step S103, defining a state function and an operation cost function of the elevator according to a loading station of the elevator, so as to obtain a state transfer equation according to the state function and the operation cost function;
and step S104, performing iterative updating according to the state transition equation based on the initial position and the starting point and the end point to obtain the driving path of the hoisting machine.
In the technical scheme provided by some embodiments of the disclosure, firstly, a part of tasks are selected according to the priority of the tasks to be executed in the current production environment for scheduling and planning of the hoist, then, a state function is established by using a dynamic planning method to obtain a state transition equation, iterative solution is performed by optimizing the operation cost of the hoist, and finally, the running path of the hoist is obtained to complete scheduling and planning. According to the elevator scheduling method, on one hand, the task execution sequence can be adjusted according to the requirements of the current production environment, and the tasks with high priority can be preferentially executed, so that the elevator execution tasks are adaptive to the current production requirements, and the benefits are maximized; on the other hand, a solving method is provided for planning the operation path of the elevator with a plurality of loading stations, the global optimization of the operation path of the elevator within a certain task quantity can be realized, the utilization rate of the loading stations of the elevator is improved, the dead time of the elevator is reduced, and the operation cost is saved.
Next, the steps of the elevator dispatching method in this exemplary embodiment will be described in more detail with reference to the drawings and examples.
In step S101, a preset number of tasks are selected as tasks to be planned based on priorities of tasks to be executed by the hoist; wherein the elevator has a plurality of loading stations.
In one embodiment of the disclosure, the elevator is provided with multiple loading stations, so that multiple tasks can be executed simultaneously, and a certain number of tasks can be selected for scheduling and planning in consideration of the complexity of model solution, so as to realize global optimization of the elevator path in the selected tasks.
Therefore, a preset number of tasks need to be selected from the tasks to be executed by the elevator as the tasks to be planned. Specifically, the more important task priority can be selected according to the task priority for planning.
Further, executing step S101 specifically includes the following two steps:
performing priority gradient sequencing on the tasks to obtain tasks corresponding to the priorities respectively;
and (II) selecting a preset number of tasks from the tasks corresponding to the priorities in sequence from high to low according to the priorities as tasks to be planned.
For step (one), fig. 2 schematically shows a flow diagram of a priority gradient ranking method in an exemplary embodiment of the disclosure. Referring to fig. 2, the task priority gradient sorting specifically includes the following steps:
step S201, determining tasks corresponding to the first priority based on the service levels of the tasks;
step S202, determining tasks corresponding to a second priority according to container positions corresponding to tasks except the tasks corresponding to the first priority;
step S203, calculating the waiting time of each task except the tasks corresponding to the first priority and the second priority to determine the task corresponding to a third priority;
and step S204, determining the task with the undetermined priority as the task corresponding to the fourth priority.
Specifically, in the present embodiment, four priorities are set in total, and all the tasks to be executed are subjected to gradient sorting and assigned to the four priority ladders.
In step S201, the operator may configure the service level tag for the important task by using the console, so that the priority of the task with the tag may be determined as the highest level, i.e., the task corresponding to the first priority.
In step S202, since the ex-warehouse tasks are executed preferentially when there are many ex-warehouse containers stacked on a certain shelf, the high-priority ex-warehouse task is selected as the task of the second priority using the container position corresponding to the task.
The higher the crowdedness of the layer where the container position corresponding to the ex-warehouse task is located (or the lower the scarcity of the container position), the higher the priority is, that is, the priority of the ex-warehouse task is determined according to the number of the tasks to be ex-warehouse in the current layer.
Specifically, the number of the boxes to be delivered from the warehouse on the layer storage position where the warehouse-out task i is located is set as aiThe bins to be taken out of the storage positions form a set A when aiAnd when the preset threshold (for example, 75%) of the set A is exceeded, marking the task i as a high-priority task, and determining the task i as a task corresponding to the second priority.
It should be noted that, when determining the second priority, it is necessary to remove the task corresponding to the first priority and select the task to be executed preferentially from the remaining tasks.
In step S203, the longer the task waiting time is, the higher the outbound tasks are executed preferentially, so the higher-priority outbound task is selected as the third-priority task using the waiting time of the task.
Specifically, the system will time-tag the task as it is generated, and when the task is selected, the system will sum up the current timeTask generation time calculation waiting duration tiThe waiting time of all the tasks to be executed form a set T, and when T is reachediAnd when the preset threshold (for example, 75%) of the set T is exceeded, marking the task i as a high-priority task, and determining the task i as a task corresponding to the third priority.
It should be noted that, similarly to the synchronization step S202, when determining the third priority, it is necessary to remove the tasks corresponding to the first and second priorities and select the task to be executed with priority from the remaining tasks.
In step S204, the remaining tasks with no determined priority are automatically categorized into a fourth priority.
For step (two), fig. 3 schematically shows a flow chart of a method for selecting a task to be planned in an exemplary embodiment of the disclosure. Referring to fig. 3, selecting a task to be planned specifically includes the following steps:
step S301, initializing a task set to be selected and a selected task set, and configuring the initial value of the number of the tasks to be selected as the preset number;
step S302, determining a target priority according to the priorities of the tasks in the task set to be selected from high to low;
step S303, when the number of the tasks corresponding to the target priority is smaller than the number of the tasks to be selected, all the tasks corresponding to the target priority are selected; or
Step S304, when the number of the tasks corresponding to the target priority is larger than the number of the tasks to be selected, selecting the tasks matched with the number of the tasks to be selected from the tasks corresponding to the target priority;
step S305, updating the task set to be selected, the selected task set and the number of the tasks to be selected based on the selected tasks;
and S306, repeating the steps of determining the target priority, selecting the tasks and updating until the number of the tasks to be selected is zero, and taking the tasks in the selected task set as the tasks to be planned.
Specifically, two sets are set when selecting tasks, one is a task set W to be selected which is formed by tasks to be executed which can be used for selection, the other is a selected task set U which is formed by selected tasks, and meanwhile, the number n of tasks to be selected is set. The task candidate task set W to be executed, the selected task set U and the number n of tasks to be selected are changed after each round of task selection.
It should be noted that, before performing step 301 to step 306, the quantitative relationship between W and n may be determined first. If | W | ≦ n, then U ═ U ≦ W, that is, all tasks to be executed are planned when the number of tasks to be executed is less than the number that needs to be selected. And on the contrary, when the absolute value of W is larger than N, the N tasks are required to be selected from the W in sequence according to the priority.
Next, steps 301 to 306 of selecting N tasks will be explained in detail.
In step S301, a task set to be selected and a selected task set are initialized, and an initial value of the number of tasks to be selected is configured as the preset number.
Firstly, initializing a task set W to be selected and a selected task set U, wherein in an initial state, the task set W to be selected comprises all tasks to be executed, and the selected task set U is an empty set.
And then configuring an initial value of the number n of the tasks to be selected. Assuming that N tasks are required to be selected for planning in the scheduling of the elevator, when the elevator is in an idle state, that is, there are no tasks in execution, the initial value of the number N of tasks to be selected is the preset number N.
In step S302, a target priority is determined according to the priorities of the tasks in the task set to be selected from high to low.
Specifically, the priority corresponding to each task is determined in advance, and the highest priority in the current task set W to be selected is determined as the target priority. In the first round of selection, if the task set W to be selected includes all tasks, the determined target priority is the first priority, and if all the tasks of the first priority are selected in the subsequent task selection, the selected tasks are not included in the task set W to be selected, and the target priority may be the second priority after the first priority.
And comparing the task number corresponding to the target priority with the task number n to be selected so as to select the tasks according to different methods.
In step S303, when the number of tasks corresponding to the target priority is smaller than the number of tasks to be selected, all tasks corresponding to the target priority are selected.
Specifically, the number of the tasks to be selected is n, and if the number of the tasks corresponding to the target priority is less than n, all the tasks of the target priority are added to the selected task set U, that is, all the tasks corresponding to the target priority are selected.
In step S304, when the number of tasks corresponding to the target priority is greater than the number of tasks to be selected, a number of tasks matching the number of tasks to be selected is selected from the tasks corresponding to the target priority.
Alternatively, when the number of tasks corresponding to the target priority is greater than n, n tasks are selected from the tasks corresponding to the target priority. In practical applications, in order to improve the execution efficiency of the elevator and reduce the idle rate, similar tasks are usually scheduled to be executed in a combined manner.
Further, in step S304, the selecting a task whose number matches the number of tasks to be selected from the tasks corresponding to the target priority includes: when non-grouped tasks exist in the selected task set, calculating the similarity between the non-grouped tasks and the tasks corresponding to the target priority, and selecting the tasks matched with the number of the tasks to be selected according to the similarity; or when non-grouped tasks do not exist in the selected task set, selecting one task from the tasks corresponding to the target priority according to the current position information of the hoister, and calculating the similarity between the selected task and all the tasks corresponding to the target priority except the selected task, so as to select the tasks matched with the number of the tasks to be selected according to the similarity.
Wherein ungrouped tasks are relative to ganged tasks. The tasks are related to four types including an ex-warehouse downward task, an ex-warehouse upward task, a warehouse downward task and a warehouse downward task, and the types of the tasks are determined when the tasks are established. If the number of tasks of the same type is multiple of the total loading station number of the elevator, the tasks are called grouped tasks, and the tasks are called fee renting tasks correspondingly.
For example, if the total number of loading stations of the elevator is 3, the total number of tasks going out of the warehouse is 3, and the total number of tasks going out of the warehouse is 1, then 3 tasks going out of the warehouse going downward are grouped tasks, and 1 task going out of the warehouse going upward is not grouped tasks.
If non-grouped tasks exist in the selected tasks, the non-grouped tasks need to be preferentially considered to be changed into grouped tasks so as to facilitate the elevator to execute the tasks when the tasks are selected. Therefore, the similarity between all tasks in the target priority and non-grouped tasks needs to be calculated, and then n-tasks are selected in sequence from high to low according to the similarity.
If there are a plurality of ungrouped tasks (for example, 2), similarity between all tasks (for example, 6) in the target priority and the plurality of ungrouped tasks needs to be calculated, and then task selection is performed from high to low among all the similarities (that is, 2 × 6 — 12).
If non-grouped tasks do not exist in the selected tasks, the tasks which are selected before do not need to be considered when the tasks are selected, so that the method is the same as the method for selecting the tasks without the previous priority, 1 task is selected nearby according to the current position of the hoister, and then n-1 tasks are selected in sequence from high to low according to the similarity between the task and other tasks.
Wherein the start and end points of tasks are known at the time of creation of each task, e.g. i the start point of a task is piEnd point is pi', then the similarity r between task i and task jijAs shown in equation (1):
in step S305, the task set to be selected, the selected task set, and the number of tasks to be selected are updated based on the selected task.
Specifically, the selected tasks are removed from the task set to be selected and added to the selected task set, and then the number of the tasks to be selected is changed according to the number of the selected tasks.
And S306, repeating the steps of determining the target priority, selecting the tasks and updating until the number of the tasks to be selected is zero, and taking the tasks in the selected task set as the tasks to be planned.
For example, if the priorities are sorted, the first priority corresponds to 3 tasks, namely, the first task, the second task and the third task, the second priority corresponds to 5 tasks, namely, the fourth task, the fifth task, the sixth task, the seventh task and the seventh task, and N is required to be selected to be 5 tasks, and the task selecting process is as follows:
firstly, initializing a task set W to be selected (i, ii, iii, iv, v, c, v), and selecting a task set W
And the number N of the tasks to be selected is equal to N and equal to 5.
And then, determining that the target priority is a first priority, wherein 3 tasks corresponding to the first priority are less than 5, so that the tasks of the first priority are selected completely, updating a task set to be selected into W (r, c, and r), and updating a selected task set into U (r, c, and c), wherein the task (r) and the task (r) are not grouped, the task (r) is a non-grouped task, and the number n of the tasks to be selected is 5-3 (2).
Then, the target priority is determined to be the second priority, and the number of the tasks corresponding to the second priority is 5, and 5 is greater than 2, so that 2 tasks need to be selected from the 5 tasks of the second priority. Because the task (c) is not a grouped task, the similarity between the task (c) and each task in the second priority level needs to be calculated, and then the similarity x between the task (c) and the task (c), and the task (c) is calculated according to the similarity x between the task (c) and the task (c), and the task (c)34、x35、x36、x37、x38The values of (A) and (B) are sequentially selected from 2 similarity degreesThe highest tasks, such as task (c) and task (c).
After the selection is finished, the number n of the tasks to be selected is 0, which indicates that the task selection is finished, the selected task set U is { ((r), (c), and (c) }, and then the tasks { ((r), (c), and (b) } in the task set W to be selected are the tasks to be executed which are not selected, and can be placed in the task set to be selected in the next planning.
In one embodiment of the present disclosure, planning may be performed in real time during the performance of a task, in addition to when the elevator is idle.
Specifically, when there are tasks in execution in the elevator, after initializing the candidate task set and the selected task set and configuring the initial value of the number of the candidate tasks to the preset number, the method further includes: adding the executing task to the selected task set; and updating the number of the tasks to be selected according to the number of the executed tasks.
Because the elevator is provided with a plurality of loading stations, a plurality of warehousing and ex-warehousing tasks can be executed at the same time, if the elevator still has executing tasks, for example, containers still need to be warehoused on the loading stations, or the target containers need to be taken out in the scheduling, the executing tasks need to be added into the selected task set at the moment. The task under execution is composed into a task set E, and after the selected task set U is initialized, the task under execution needs to be added to the selected task set U, i.e., U ═ E.
In step S102, an initial position of the hoist and a start point and an end point corresponding to each task to be planned are obtained.
Specifically, before planning, some known information needs to be obtained, including the initial position of the hoisting machine and the starting point and the end point of the operation of the hoisting machine corresponding to each task to be planned.
The position of the hoister is mainly determined by two parameters, namely the position of the hoister and a positioning platform of the hoister, and the two parameters determine which platform of the hoister is opposite to which layer, namely the position of the hoister. In the initial planning state, the initial position can be obtained by acquiring the position of the hoister and the information of the positioning platform.
In addition, each task i is created in the warehousing system, and the starting point and the ending point of the operation of the hoist corresponding to the task, namely the position to which the hoist is transported from that position, are added.
In step S103, a state function and an operation cost function of the hoist are defined according to the loading station of the hoist, so as to obtain a state transition equation according to the state function and the operation cost function.
Specifically, step S103 mainly includes three steps:
step one, defining a state function of the elevator;
step two, defining an operation cost function of the elevator;
step three, constructing a state transition equation;
for convenience of description, the variables in step S103 are first introduced.
I: and the set of tasks I to be planned, wherein I is N, and N tasks to be planned are total.
P: the position is the position where the elevator stops, which may also be referred to as a stop point, starting from the initial position P, and each task requires the elevator to move the container from the starting point to the end point, so that the elevator schedules N tasks, which need to go through 2N +1 stop points in total.
F: carry thing station F set, F is No. 1 year thing station "," No. 2 year thing station ", … }
It should be noted that although the points at which the hoist needs to stop are known before planning a task, since the hoist executes a plurality of tasks at the same time, the execution order between the stop points is not determined, and a fine path planning is required.
Further, defining a state function of the hoist for step (one) includes: defining the state function according to the position of the elevator, the carrying station, the tasks to be planned, the execution state of each task to be planned and the carrying station of each task to be planned, as shown in a formula (2):
Sk＝[(p,f,i),(t1,f1,t2,f2,...,tN,fN)] (2)
wherein p is the position of the hoister; f is a loading station of the elevator; i is the ith task to be planned; t is tiFor the execution state of the ith task to be planned, the execution state comprises the execution completion, the execution in the middle and the non-execution, namely tiE { the execution is completed, and in the execution, the execution is not executed }, I belongs to I; f. ofiThe loading station used for the ith task to be planned, i.e. fiBelongs to F, I belongs to I; and N is the total number of tasks to be planned.
Further, defining an operation cost function of the elevator for the step (two), which comprises: calculating the running cost of the elevator according to the running distance between two states of the elevator and the running distance of the used carrying station so as to define the running cost function as follows:
C(Sk,Sk+1)＝xpp′×(dpp′+α×lpp′×dpp′) (3)
wherein, C (S)k,Sk+1) For the elevator from state SkTo state Sk+1The running cost of (c); p and p' are respectively the states S of the elevatorkTo state Sk+1The starting point and the end point of the operation; x is the number ofpp′A 0-1 variable indicating whether a path exists between p and p',
dpp′the running distance of the elevator from p to p'; l. thepp′The number of used loading stations in the process of moving the elevator from p to p', namely the number of tasks in the process of executing the elevator; and alpha is a weight coefficient.
Further, for the step (three) to construct the state transition equation, see formula (4):
C(Sk)＝min{C(Sk,Sk+1)+C(Sk+1)} (4)
wherein, C (S)k) For the elevator in state SkThe cost of operation; c (S)k,Sk+1) For elevator from state SkTo state Sk+1The running cost of (c); c (S)k+1) For the elevator in state Sk+1The running cost of the time.
In step S104, iteratively updating according to the state transition equation based on the initial position and the start point and the end point to obtain a driving path of the hoist.
Step S104 is a process of dynamic programming solution. The current state in dynamic programming often depends on the state of the previous stage and the decision result of the previous stage, for example, we know the state S of the kth stagekThen state S of the k +1 stagek+1Then it is determined, otherwise, the state S is knownk+1Reversible deduced state Sk。
The method comprises the steps that programming can be carried out according to a state transition equation through a known initial position of the hoist and the starting point and the end point of each task to be planned to solve a dynamic planning problem, finally, the state of the hoist corresponding to each stage k is obtained, the state of each stage comprises the position to be reached by the hoist, the executed task, the objective table of the executed task and the state information of task execution, the information of all stages are connected in series, and finally, the path planning aiming at all selected tasks to be planned is obtained by taking the current initial position of the hoist as the starting point.
Fig. 4 schematically illustrates a flow chart of a method for scheduling hoists in an exemplary embodiment of the present disclosure. Referring to fig. 4, the method mainly includes the following steps:
in step S401, information is input. The method comprises the following steps of firstly, acquiring information including the position of a hoist, a positioning platform, a task in execution (if the task is input, the task is not input if the task is input), a task to be executed, the position duration of the task and the like;
step S402, selecting tasks, namely selecting N tasks to be planned;
step S403, dynamic planning is performed. Planning the path of the hoist for the N tasks to be planned according to a state transition equation;
in step S404, information is output. And outputting the planning results of the N tasks to be planned, namely the running path of the N tasks executed by the elevator and the unplanned tasks except the N tasks to be planned.
Based on the method, on one hand, the elevator scheduling method provided by the disclosure selects the tasks according to the priority, and can adjust the task execution sequence according to the requirement of the current production environment, so that the elevator executes the tasks to be adaptive to the current production requirement; on the other hand, the global optimization of paths in a certain task quantity can be realized, the no-load of the hoister is reduced, and the utilization rate of multilayer stations is improved.
Fig. 5 schematically illustrates a composition diagram of a hoisting machine scheduling apparatus in an exemplary embodiment of the disclosure, and as shown in fig. 5, the hoisting machine scheduling apparatus 500 may include a selecting module 501, an obtaining module 502, a modeling module 503, and a solving module 504. Wherein:
a selecting module 501, configured to select a preset number of tasks as tasks to be planned based on priorities of tasks to be executed by the elevator; wherein the elevator is provided with a plurality of loading stations;
an obtaining module 502, configured to obtain an initial position of the hoist and a start point and an end point corresponding to each task to be planned;
the modeling module 503 is configured to define a state function and an operation cost function of the hoist according to the loading station of the hoist, so as to obtain a state transfer equation according to the state function and the operation cost function;
and the solving module 504 is configured to perform iterative update according to the state transition equation based on the initial position and the starting point and the end point to obtain a driving path of the hoist.
According to an exemplary embodiment of the present disclosure, the selecting module 501 includes a sorting unit and a selecting unit, where the sorting unit is configured to perform priority gradient sorting on the tasks to obtain tasks corresponding to each priority; the selecting unit is used for selecting a preset number of tasks from the tasks corresponding to the priorities in sequence from high to low according to the priorities to serve as the tasks to be planned.
According to an exemplary embodiment of the disclosure, the sorting unit is configured to determine, based on a service level of each task, a task corresponding to a first priority; determining tasks corresponding to a second priority according to container positions corresponding to tasks except the tasks corresponding to the first priority; calculating the waiting time of each task except the tasks corresponding to the first priority and the second priority so as to determine the task corresponding to a third priority; and determining the task with the undetermined priority as the task corresponding to the fourth priority.
According to an exemplary embodiment of the present disclosure, the selecting unit is configured to initialize a task set to be selected and a selected task set, and configure an initial value of a number of tasks to be selected as the preset number; determining a target priority according to the priorities of the tasks in the task set to be selected from high to low; when the number of the tasks corresponding to the target priority is smaller than the number of the tasks to be selected, all the tasks corresponding to the target priority are selected; or when the number of the tasks corresponding to the target priority is larger than the number of the tasks to be selected, selecting the tasks matched with the number of the tasks to be selected from the tasks corresponding to the target priority; updating the task set to be selected, the selected task set and the number of the tasks to be selected based on the selected tasks; and repeating the steps of determining the target priority, selecting the tasks and updating until the number of the tasks to be selected is zero, and taking the tasks in the selected task set as the tasks to be planned.
According to an exemplary embodiment of the disclosure, the selecting unit is further configured to calculate a similarity between the ungrouped task and the task corresponding to the target priority when ungrouped tasks exist in the selected task set, so as to select a task matching the number of tasks to be selected according to the similarity; or when non-grouped tasks do not exist in the selected task set, selecting one task from the tasks corresponding to the target priority according to the current position information of the hoister, and calculating the similarity between the selected task and all the tasks corresponding to the target priority except the selected task, so as to select the tasks matched with the number of the tasks to be selected according to the similarity.
According to an exemplary embodiment of the disclosure, the selecting unit is further configured to add the executing task to the selected task set when the elevator has the executing task; and updating the number of the tasks to be selected according to the number of the executed tasks.
According to an exemplary embodiment of the present disclosure, the modeling module 503 includes a state function unit, configured to define the state function according to the position of the hoist, the loading station, the tasks to be planned, the execution state of each task to be planned, and the loading station of each task to be planned as follows:
Sk＝[(p,f,i),(t1,f1,t2,f2,...,tN,fN)]；
wherein p is the position of the hoister; f is a loading station of the elevator; i is the ith task to be planned; t is tiThe method comprises the steps of obtaining an execution state of an ith task to be planned, wherein the execution state comprises execution completion, execution in the middle and non-execution; f. ofiA carrying station used for the ith task to be planned; and N is the total number of tasks to be planned.
According to an exemplary embodiment of the present disclosure, the modeling module 503 includes an operation cost function unit for calculating an operation cost of the hoist according to an operation distance between two states of the hoist and an operation distance of a used loading station to define the operation cost function as:
C(Sk,Sk+1)＝xpp′×(dpp′+α×lpp′×dpp′)；
wherein, C (S)k,Sk+1) For elevator from state SkTo state Sk+1The running cost of (c); p and p' are respectively the states S of the elevatorkTo state Sk+1The starting point and the end point of the operation; x is the number ofpp′Is a 0-1 variable representing whether a path exists between p and p'; dpp′The running distance of the elevator from p to p'; lpp′The number of used loading stations in the process of moving the elevator from p to p'; and alpha is a weight coefficient.
According to an exemplary embodiment of the present disclosure, the state transition equation is:
C(Sk)＝min{C(Sk,Sk+1)+C(Sk+1)}；
wherein, C (S)k) For the elevator in state SkThe cost of operation of the process; c (S)k,Sk+1) For elevator from state SkTo state Sk+1The running cost of (c); c (S)k+1) For the elevator in state Sk+1The running cost of the time.
The specific details of each module in the elevator dispatching device 500 have been described in detail in the corresponding elevator dispatching method, and therefore are not described herein again.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
In an exemplary embodiment of the present disclosure, there is also provided a storage medium capable of implementing the above-described method. Fig. 6 schematically illustrates a schematic diagram of a computer-readable storage medium in an exemplary embodiment of the disclosure, and as shown in fig. 6, a program product 600 for implementing the above method according to an embodiment of the disclosure is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a mobile phone. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided. Fig. 7 schematically shows a structural diagram of a computer system of an electronic device in an exemplary embodiment of the disclosure.
It should be noted that the computer system 700 of the electronic device shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of the application of the embodiments of the present disclosure.
As shown in fig. 7, the computer system 700 includes a Central Processing Unit (CPU)701, which can perform various appropriate actions and processes according to a program stored in a Read-Only Memory (ROM) 702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for system operation are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An Input/Output (I/O) interface 705 is also connected to the bus 704.
The following components are connected to the I/O interface 705: an input portion 706 including a keyboard, a mouse, and the like; an output section 707 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a Network interface card such as a LAN (Local Area Network) card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.
In particular, the processes described below with reference to the flowcharts may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709, and/or installed from the removable medium 711. The computer program, when executed by a Central Processing Unit (CPU)701, performs various functions defined in the system of the present disclosure.
It should be noted that the computer readable medium shown in the embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM), a flash Memory, an optical fiber, a portable Compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.
As another aspect, the present disclosure also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs, which when executed by one of the electronic devices, cause the electronic device to implement the method described in the above embodiments.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice in the art to which the disclosure pertains.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (12)
1. A method for dispatching a hoisting machine is characterized by comprising the following steps:
selecting a preset number of tasks as tasks to be planned based on the priority of the tasks to be executed by the elevator; wherein the elevator is provided with a plurality of loading stations;
acquiring an initial position of the hoister and a starting point and a terminal point which correspond to each task to be planned respectively;
defining a state function and an operation cost function of the elevator according to a loading station of the elevator, so as to obtain a state transfer equation according to the state function and the operation cost function;
and carrying out iterative updating according to the state transition equation based on the initial position and the starting point and the end point to obtain the running path of the hoister.
2. The method for dispatching the hoisting machines according to claim 1, wherein the selecting a preset number of tasks as the tasks to be planned based on the priority of the tasks to be executed by the hoisting machines comprises:
performing priority gradient sequencing on the tasks to obtain tasks corresponding to the priorities respectively;
and selecting a preset number of tasks from the tasks corresponding to the priorities in sequence from high to low according to the priorities as tasks to be planned.
3. The elevator dispatching method as claimed in claim 2, wherein said prioritizing the tasks comprises:
determining tasks corresponding to the first priority based on the service levels of the tasks;
determining tasks corresponding to a second priority according to container positions corresponding to tasks except the tasks corresponding to the first priority;
calculating the waiting time of each task except the tasks corresponding to the first priority and the second priority so as to determine the task corresponding to a third priority;
and determining the task with the undetermined priority as the task corresponding to the fourth priority.
4. The method for dispatching the hoisting machines according to claim 2, wherein the step of selecting a preset number of tasks from the tasks corresponding to the priorities in sequence from high to low as the tasks to be planned comprises the steps of:
initializing a task set to be selected and a selected task set, and configuring the initial value of the number of the tasks to be selected as the preset number;
determining a target priority according to the priorities of the tasks in the task set to be selected from high to low;
when the task number corresponding to the target priority is smaller than the task number to be selected, all tasks corresponding to the target priority are selected; or
When the number of the tasks corresponding to the target priority is larger than the number of the tasks to be selected, selecting the tasks with the number matched with the number of the tasks to be selected from the tasks corresponding to the target priority;
updating the task set to be selected, the selected task set and the number of the tasks to be selected based on the selected tasks;
and repeating the steps of determining the target priority, selecting the tasks and updating until the number of the tasks to be selected is zero, and taking the tasks in the selected task set as the tasks to be planned.
5. The method for dispatching the elevators as recited in claim 4, wherein the selecting the tasks with the number matched with the number of the tasks to be selected from the tasks corresponding to the target priority comprises:
when non-grouped tasks exist in the selected task set, calculating the similarity between the non-grouped tasks and the tasks corresponding to the target priority, and selecting the tasks matched with the number of the tasks to be selected according to the similarity; or
And when non-grouped tasks do not exist in the selected task set, selecting one task from the tasks corresponding to the target priority according to the current position information of the hoister, and calculating the similarity between the selected task and all the tasks corresponding to the target priority except the selected task, so as to select the tasks matched with the number of the tasks to be selected according to the similarity.
6. The method as claimed in claim 4, wherein when there are tasks in execution in the elevator, after the initializing the candidate task set and the selected task set and configuring the initial value of the number of the candidate tasks to the preset number, the method further comprises:
adding the executing task to the selected task set;
and updating the number of the tasks to be selected according to the number of the executed tasks.
7. The method for dispatching a hoist as claimed in claim 1, wherein the defining a state function of the hoist according to the loading station of the hoist comprises:
defining the state function as follows according to the position of the elevator, the carrying station, the tasks to be planned, the execution state of each task to be planned and the carrying station of each task to be planned:
Sk＝[(p,f,i),(t1,f1,t2,f2,...,tN,fN)]；
wherein p is the position of the hoister; f is a loading station of the elevator; i is the ith task to be planned; t is tiThe method comprises the steps of obtaining an execution state of an ith task to be planned, wherein the execution state comprises execution completion, execution in the middle and non-execution; f. ofiA carrying station used for the ith task to be planned; and N is the total number of tasks to be planned.
8. The method for dispatching a hoist as claimed in claim 1, wherein the defining a cost function for operating a hoist according to a loading station of the hoist comprises:
calculating the running cost of the elevator according to the running distance between two states of the elevator and the running distance of the used loading station to define the running cost function as follows:
C(Sk,Sk+1)＝xpp′×(dpp′+α×lpp′×dpp′)；
wherein, C (S)k,Sk+1) For elevator from state SkTo state Sk+1The running cost of (c); p and p' are respectively the states S of the elevatorkTo state Sk+1The starting point and the end point of the operation; x is the number ofpp′Is a 0-1 variable representing whether a path exists between p and p'; dpp′The running distance of the elevator from p to p'; lpp′The number of used loading stations in the process of moving the elevator from p to p'; α is a weight coefficient.
9. The elevator dispatching method as in claim 1, wherein the state transition equation is:
C(Sk)＝min{C(Sk,Sk+1)+C(Sk+1)}；
wherein, C (S)k) For the elevator in state SkThe cost of operation; c (S)k,Sk+1) For elevator from state SkTo state Sk+1The running cost of (c); c (S)k+1) For the elevator in state Sk+1The running cost of the time.
10. An elevator dispatching device, comprising:
the selection module is used for selecting a preset number of tasks as tasks to be planned based on the priority of the tasks to be executed by the hoister; wherein the elevator is provided with a plurality of loading stations;
the acquisition module is used for acquiring the initial position of the hoister and the starting point and the end point corresponding to each task to be planned;
the modeling module is used for defining a state function and an operation cost function of the hoister according to a loading station of the hoister so as to obtain a state transfer equation according to the state function and the operation cost function;
and the solving module is used for carrying out iterative updating according to the state transition equation based on the initial position and the starting point and the end point to obtain the driving path of the hoister.
11. A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the elevator dispatching method of any of claims 1 to 9.
12. An electronic device, comprising:
one or more processors;
a storage device to store one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the elevator dispatching method of any of claims 1-9.
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| CN117196269A (en) * | 2023-11-07 | 2023-12-08 | 深圳市欣视景科技股份有限公司 | Intelligent transfer control method based on artificial intelligence and computer program medium |
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