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A task allocation method based on task allocation coordination strategy and particle swarm algorithm

A technology of particle swarm algorithm and task allocation, which is applied in the direction of calculation, calculation model, data processing application, etc., can solve the problems of task overload, shortage, overlapping task allocation, etc., and achieve the effect of low cost and most cost

Active Publication Date: 2022-06-17
XI'AN POLYTECHNIC UNIVERSITY
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to solve the problems of task allocation overlap, task overload and the remaining or insufficient power of the robot when performing tasks in the existing allocation technology, and to provide a task allocation method based on task allocation coordination strategy and particle swarm algorithm

Method used

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  • A task allocation method based on task allocation coordination strategy and particle swarm algorithm
  • A task allocation method based on task allocation coordination strategy and particle swarm algorithm
  • A task allocation method based on task allocation coordination strategy and particle swarm algorithm

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Embodiment 1

[0088] The simulation experiment environment of this paper is on the Windows operating system, and the simulation experiment of the algorithm is realized based on the Matlab2014a environment. The PC is configured with Inter(R) Core-i5-6500@3.2GHz processor and 4G memory.

[0089] S1. Use the particle swarm algorithm to optimize the distribution radius to obtain the initial distribution result. The specific operations are as follows:

[0090]The environment is a logistics warehouse with 4 isomorphic robots. Table 1 shows the performance parameters of each robot. There are 12 tasks randomly scattered around, namely R=4, T=12, the number of particle swarms is set to 10, and the learning factor c 1 =c 2 =2,ω 0 =0.2,V 0 = 0.5, the speed range is [0, 1], and ω is set in the performance index function formula (11). 1 =0.7,ω 2 =0.2,ω 3 = 0.1. And the power consumption per unit distance of all robots is 1, the robot coordinates: R 1 (4,10), R 2 (5,40), R 3 (70,60), R 4 (20,9...

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Abstract

The invention discloses a task allocation method based on a task allocation coordination strategy and a particle swarm algorithm, comprising the following steps: 1) using the particle swarm algorithm to optimize the allocation radius to obtain an initial allocation result; 2) using the coordination strategy to adjust the initial allocation result , to complete the first assignment; 3) Repeat steps 1)‑2) to reassign unassigned tasks until the tasks are completely assigned. The task assignment method based on the task assignment coordination strategy and the particle swarm algorithm of the present invention combines the task coordination strategy with the particle swarm algorithm to solve the common task assignment overlap, task overload and The remaining or insufficient power of the robot when performing tasks.

Description

technical field [0001] The invention belongs to the field of task allocation, in particular to a task allocation method based on a task allocation coordination strategy and a particle swarm algorithm. Background technique [0002] With the gradual rise of online e-commerce, online shopping has become one of the main ways people consume. Traditional logistics warehouses have been unable to meet the ever-increasing heavy logistics tasks. The development of modern technology has made multi-robot collaboration increasingly an indispensable part of warehousing logistics. Multi-robot collaboration can replace workers in the warehouse to complete a series of tasks with high risk and difficulty, which not only improves efficiency, but also reduces the cost of completing tasks. The problem of multi-robot task assignment in warehousing and logistics is becoming a research hotspot and development direction in recent years. Multi-robot taskallocation (MRTA) means that when a robot per...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06Q10/08G06N3/00
CPCG06Q10/0631G06Q10/08G06N3/006
Inventor 陈海洋阳杰牛龙辉
Owner XI'AN POLYTECHNIC UNIVERSITY
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