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Multi-load carrying robot group multi-target task allocation scheduling optimization method

A technology of task allocation and optimization method, applied in the field of manufacturing workshop scheduling, which can solve problems such as system deadlock, power supply of carrier robots, and path conflicts of carrier robots.

Active Publication Date: 2021-02-23
HOHAI UNIV CHANGZHOU
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The first is the task selection problem, which needs to be solved whether the multi-capacity delivery robot will perform the loading task or the unloading task next.
The second is the unloading scheduling problem. If the delivery robot performs the unloading task in the next step, it needs to decide the unloading point that the delivery robot should visit
The third problem is the loading scheduling problem. If the delivery robot performs the loading task in the next step, it needs to decide the loading point that the delivery robot should visit
The carrier robot is the active object in the workpiece selection problem (the decision is made by the carrier robot itself), however, when an empty carrier robot finds that there are no workpieces to load in the system, it becomes passive and sits idle until The system issues a new loading task
[0004] The four problems of the traditional dynamic scheduling of delivery robots basically deal with the simple situation that multi-capacity delivery robots may occur when dealing with system scheduling tasks, but they do not comprehensively consider other problems that may occur in the delivery robot system, such as delivery robot path conflicts, Carrying robot power supply and system deadlock and other issues

Method used

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  • Multi-load carrying robot group multi-target task allocation scheduling optimization method
  • Multi-load carrying robot group multi-target task allocation scheduling optimization method
  • Multi-load carrying robot group multi-target task allocation scheduling optimization method

Examples

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Embodiment

[0156] In this embodiment, multiple sets of simulation experiments are carried out to compare 8 (1*2*2*2) combinations of the traditional NIPS strategy and the scheduling strategy of the present invention.

[0157] For the task selection problem, Ho Y C, Chen S H.A simulation study on the performance of task-determination rules and delivery-dispatching rules formultiple-load AGVs[J].International Journal of Production Research 2006,44(20):4193-4222.中 Three single-attribute rules are proposed and the performance among them is compared. Simulation results show that Drop-Task-First (DTF) has the best production performance. Therefore, the task selection rule adopted in this embodiment is the unloading priority rule. Under this rule, if the delivery robot is in the loading state, it will give priority to the unloading task.

[0158] For loading scheduling, two rules are selected in this embodiment, the first is the Multi-Attribute Rule for Pickup dispatching problem (MARP) in the...

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Abstract

The invention discloses a multi-load carrying robot group multi-target task allocation scheduling optimization method, which introduces a deadlock avoidance strategy in carrying robot scheduling, andproposes a loading scheduling multi-attribute rule according to two targets of time cost and conforming to bearing capacity. And a workpiece selects a multi-attribute scheduling rule and an unloadingscheduling multi-attribute rule. According to the scheduling method, deadlock can be effectively avoided, system resources can be effectively utilized, and the scheduling method is more efficient thana traditional scheduling method for the multi-load carrying robot.

Description

technical field [0001] The invention relates to a multi-objective task allocation and scheduling optimization method for a group of multi-capacity carrying robots, which belongs to the technical field of manufacturing workshop scheduling. Background technique [0002] Workshop layout and carrier robot path planning are the main contents of flexible manufacturing workshop design research, and the two have a strong coupling relationship. The path planning of the delivery robot needs to design a set of optimal collision-free paths according to the workshop layout and optimization objectives. Whether the workshop layout is reasonable or not has a great impact on the delivery robot path planning and the performance of the entire system. Therefore, when designing the delivery robot system, it is necessary to pay attention to the design of the workshop layout and the delivery robot path planning, and handle the synergy between the two. [0003] The traditional control method (Cont...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q10/08G06F30/20G06F111/06
CPCG06Q10/0631G06Q10/083G06F30/20G06F2111/06Y02P90/02
Inventor 顾文斌陈泽宇李沛霖李育鑫苑明海裴凤雀
Owner HOHAI UNIV CHANGZHOU
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