@inproceedings{c3c3354e0e014a998bc1942add9fd0c2,
title = "Flexible job shop scheduling multi-objective optimization based on improved strength pareto evolutionary algorithm",
abstract = "Scheduling for the flexible job shop is very important in fields of production management. To solve the multi-objective optimization in flexible job shop scheduling problem (FJSP), the FJSP multi-objective optimization model is constructed. The cost, quality and time are taken as the optimization objectives. An improved strength Pareto evolutionary algorithm (SPEA2+) is put forward to optimize the multi-objective optimization model parallelly. The algorithm uses a new model of a Multi-objective genetic algorithm that includes more effective crossover and could obtain diverse solutions in the objective and variable spaces to archive the Pareto optimal sets for FJSP multi-objective optimization. Then an approach based on fuzzy set theory was developed to extract one of the Pareto-optimal solutions as the best compromise one. The optimization results were compared with those obtained by NSGA-II and POS. At last, an instance of flexible job shop scheduling problem in automotive industry is given to illustrate that the proposed method can solve the multi-objective FJSP effectively.",
keywords = "Flexible job shop scheduling, Genetic algorithm, Multi-objective optimization, SPEA2+",
author = "Wei Wei and Yixiong Feng and Jianrong Tan and Ichiro Hagiwara",
year = "2011",
doi = "10.4028/www.scientific.net/AMR.186.546",
language = "英语",
isbn = "9783037850244",
series = "Advanced Materials Research",
pages = "546--551",
booktitle = "New Trends and Applications of Computer-Aided Material and Engineering",
note = "2011 International Conference on Computer-Aided Material and Engineering, ICCME 2011 ; Conference date: 09-03-2011 Through 11-03-2011",
}