Hybrid Intelligent Algorithm Solving Uncertainty Job-Shop Scheduling Problem

DOI

10.2991/ameii-16.2016.106How to use a DOI?

Keywords

Job shop scheduling, fuzzy mathematics, immune, taboo

Abstract

Researched the uncertain Job-Shop Scheduling, on the basis of the original triangular fuzzy number to describe fuzzy processing time, structured the fuzzy Job-Shop Scheduling model. Algorithm using the concept of "big valley" topology represent solution space, using strong swap mutations in early immune genetic algorithm, and implanting vaccines in three styles, rapidly improved the ability of search "mountain"; After immune selection using taboo search's "climb" idea improve the local search ability of the algorithm, so as to choose the individual with maximum satisfaction in the "big valley" quickly and efficiently. And through Matlab2012a software simulation examples verify the effectiveness of the immune genetic and taboo hybrid intelligent algorithm.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yang-Jun Hu
AU  - Cun-li Song
PY  - 2016/04
DA  - 2016/04
TI  - Hybrid Intelligent Algorithm Solving Uncertainty Job-Shop Scheduling Problem
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SP  - 528
EP  - 534
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.106
DO  - 10.2991/ameii-16.2016.106
ID  - Hu2016/04
ER  -