Modified Binary Particle Swarm Optimization Algorithm in Lot-Splitting Scheduling Involving Multiple Techniques

Abstract

This paper aims to strike a balance between cost, time and quality of multi-technique, multi-process flexible job-shop scheduling problem (FJSP) and thus improve the overall performance of the FJSP model. For this purpose, a bi-objective planning model was established for multi-technique, multiprocess FJSP according to the multi-objective planning method in operational theory. Then, the structure of solution was designed for the established model, and the binary particle swarm optimization (BPSO) algorithm was modified to simulate the proposed method. Through the simulation, the following conclusions were put forward: (1) The established bi-objective planning model for multi-technique, multi-process FJSP meet the general requirements of manufacturing enterprises, laying the basis for further modification and derivation; (2) The modified BPSO (MBPSO) algorithm can solve the said model in a stable, fast and accurate manner. The research findings shed theoretical new light on the solution and application of real-world multi-technique, multi-process FJSP and provide practical guidance for the flow shop enterprises to improve their scheduling plans.

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