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AGV optimization scheduling method based on mixed particle swarm optimization

A hybrid particle swarm and optimal scheduling technology, applied in computing, computing models, genetic models, etc.

Active Publication Date: 2015-03-11
SHANGHAI JINGXING LOGISTICS EQUIP ENGCO
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Problems solved by technology

[0006] The purpose of the present invention is to provide an AGV optimal scheduling method based on the hybrid particle swarm algorithm, which solves the problem of optimal scheduling of the automatic three-dimensional warehouse transportation system

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  • AGV optimization scheduling method based on mixed particle swarm optimization
  • AGV optimization scheduling method based on mixed particle swarm optimization
  • AGV optimization scheduling method based on mixed particle swarm optimization

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Embodiment Construction

[0048] specific implementation

[0049] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0050] The present invention is based on the mixed particle swarm algorithm AS / RS transportation system AGV optimal scheduling method, which is specifically implemented according to the following steps:

[0051] Step 1: Set the pick-up / down-package station, entry / exit station (I / O station) and AGV as scheduling objects, abstract their working process into a mathematical model, and determine the objective function of the scheduling plan.

[0052] The goal of AGV optimal scheduling is to find an effective scheduling strategy that can minimize the time it takes for AGV to complete the delivery task. The mathematical model is expressed as follows:

[0053] First define some parameters as follows:

[0054] n: the total number of entry / exit stations;

[0055] S={1,2,...,n}: set of serial number of entry / exit station;

...

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Abstract

The invention relates to an AGV optimization scheduling method based on mixed particle swarm optimization. First of all, a mathematics model is abstracted from the work process of an AGV, and an object function of a scheduling scheme is determined, and secondly, the model is solved by use of the mixed particle swarm optimization based on a genetic algorithm, a stimulated annealing algorithm and ant colony optimization, and an optimization scheduling scheme is generated. According to the invention, a contrast analysis is made between the mixed particle swarm optimization and standard particle swarm optimization through examples, and the variation operation of the mixed optimization employs an ant colony optimization thinking mode, ensures intersection of individual best and group best in an intersection operation process, ensures the feasibility of the mixed particle swarm optimization and has the validity for solving large-scale scheduling tasks.

Description

technical field [0001] The invention belongs to the technical field of automatic three-dimensional warehouse optimal scheduling, relates to an AGV optimal scheduling method, in particular to an automatic three-dimensional warehouse transportation system AGV optimal scheduling method based on a genetic algorithm, a simulated annealing algorithm and an ant colony algorithm mixed particle swarm algorithm. Background technique [0002] The research and development of AS / RS (Automated Storage and Retrieval System) system hardware equipment has tended to be complete. Modern enterprises have increased requirements for AS / RS work efficiency, and more focus on system optimization management, scheduling and job optimization. The conveying system of AS / RS has become the bottleneck affecting the warehouse operation, so it is necessary to adopt a suitable method to solve the problem of AGV optimal scheduling of the conveying system, so as to increase the working efficiency of the warehous...

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Application Information

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IPC IPC(8): G06Q10/08G06N3/00G06N3/12
CPCG06N3/00G06N3/126G06Q10/08
Inventor 杨玮李国栋李程曹薇高贺云杨超群
Owner SHANGHAI JINGXING LOGISTICS EQUIP ENGCO
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