Block-based Evolutionary Algorithm for Permutation Flow-shop Scheduling Problem

Authors

Xiaobing Pei, College of Management, Tianjin University of Technology, Tianjin 300384, China;
Zhao Heng, College of Management, Tianjin University of Technology, Tianjin 300384, China;

Abstract

Abstract: To solve the permutation flow-shop scheduling problem(PFSP), an effective new global evolutionary algorithm based on block model is developed. The probability model is built based on the information of job position through sample and statistic on the good chromosomes, and the association rule is applied to extract continuous or discontinuous blocks which contain job information respectively. The superiority blocks with position probability model for artificial chromosome combinations are integrated. The disadvantage gene is excavated according to the inferior chromosome and used for the later mutation operation. Two efficient local search methods called position model-based interchange and NEH-based insertion are proposed to further filter the dominant solution. Simulation results on Reeves and Taillard suites and comparisons with other well-known algorithms validate its excellent searching ability and efficiency of the proposed algorithm.

Recommended Citation

Pei, Xiaobing and Heng, Zhao (2019) "Block-based Evolutionary Algorithm for Permutation Flow-shop Scheduling Problem," Journal of System Simulation: Vol. 30: Iss. 8, Article 43.
DOI: 10.16182/j.issn1004731x.joss.201808043
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss8/43

First Page

3170

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201808043

Last Page

3178

CLC

TP301

Recommended Citation

Pei Xiaobing, Zhao Heng. Block-based Evolutionary Algorithm for Permutation Flow-shop Scheduling Problem[J]. Journal of System Simulation, 2018, 30(8): 3170-3178.

DOI

10.16182/j.issn1004731x.joss.201808043