Job-shop multi-target scheduling method with limited transportation capacity constraint

Abstract

The invention relates to the technical field of job shop scheduling, in particular to a multi-target scheduling method for a job shop constrained by limited transportation capacity, which comprises the following steps: constructing a multi-target scheduling scene of the job shop constrained by the limited transportation capacity according to an actual production shop; determining scheduling parameters and preconditions of a multi-target scheduling scene of the job shop; constructing a multi-target workshop scheduling model with double constraints of transportation resources and processing equipment resources; analyzing the multi-target workshop scheduling model based on a multi-target Moine algorithm; obtaining the optimal minimum maximum completion time and the minimum AGV total transportation time according to the analysis result, and outputting a multi-target scheduling scheme of the job shop according to the optimal minimum maximum completion time and the minimum AGV total transportation time; according to the method, a reasonable joint scheduling scheme is formulated in a limited transportation capacity constraint scene, so that the manufacturing system has better processing efficiency, and the transportation consumption of the AGV can be reduced.

Description

technical field [0001] The invention relates to the technical field of job shop scheduling, in particular to a job shop multi-objective scheduling method constrained by limited transportation capacity. Background technique [0002] For traditional job shop scheduling problem research, it often does not consider the transfer process of workpieces / materials between equipment in the solution process, or assumes the transfer time as a fixed value of transportation time. However, in the actual manufacturing system, the material handling cost generated by the handling activities associated with workpieces / materials during the product manufacturing process usually accounts for 15% to 70% of the product manufacturing cost, and usually requires 25% of human resources, 55% of the factory space and 87% of the production time, so it is particularly important to consider the impact of the flow of materials / workpieces between various equipment when formulating workshop production scheduli...

AI Technical Summary

Problems solved by technology

However, in the actual production and manufacturing system, affected by factors such as equipment procurement costs, workshop layout design, and actual workshop operation, the material storage and transportation system constructed by AGV and other handling equipment can provide limited transportation capacity, and cannot guarantee that all handling tasks will be generated You can get the response from the AGV at any time (complete the processing task and wait for the sequence)

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