Three hybridization models based on local search scheme for job shop scheduling problem

3rd International Conference on Manufacturing, Optimization, Industrial and Material Engineering

Fraga, Tatiana Balbi^1

Department of Production Engineering, Centro Acadêmico Do Agreste, Universidade Federal de Pernambuco, Caruaru, PE, Brazil^1

关键词: Hybrid model;    Job shop scheduling problems;    Local search;    Local search heuristics;    Original algorithms;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/83/1/012001/pdf
DOI  :  10.1088/1757-899X/83/1/012001

来源: IOP

【 摘 要 】

This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.