Solving flexible job shop scheduling problems with transportation time based on improved genetic algorithm-Reference-Cited by-同舟云学术

Solving flexible job shop scheduling problems with transportation time based on improved genetic algorithm

Published:2019 Issue:3 Volume:16 Page:1334-1347
ISSN:1547-1063
Container-title:Mathematical Biosciences and Engineering
language:en
Short-container-title:

Author:

Zhang Guohui, ,Sun Jinghe,Liu Xing,Wang Guodong,Yang Yangyang

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modelling and Simulation,General Medicine

Reference3 articles.

1. X. Y. Li, L. Gao, Q. K. Pan, et al., An effective hybrid genetic algorithm and variable neighborhood search for integrated process planning and scheduling in a packaging machine workshop, IEEE T. Syst. Man. Cy. A., (2018),

2. B. Naderi, A. A. Javid and F. Jolai, Permutation flowshops with transportation

3. S. Karimi, Z. Ardalan and B. Naderi, et al., Scheduling flexible job-shops with transportation

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