Diversifying TS using GA in Multi-agent System for Solving Flexible Job Shop Problem

Ameni Azzouz, Meriem Ennigrou, Boutheina Jlifi

Abstract

No doubt, the flexible job shop problem (FJSP) has an important significance in both fields of production management and combinatorial optimization. For this reason, FJSP continues to attract the interests of researchers both in academia and industry. In this paper, we propose a new multi-agent model for FJSP. Our model is based on cooperation between genetic algorithm (GA) and tabu search (TS). We used GA operators as a diversification technique in order to enhance the searching ability of TS. The computational results confirm that our model MAS-GATS provides better solutions than other models.

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Paper Citation


in Harvard Style

Azzouz A., Ennigrou M. and Jlifi B. (2015). Diversifying TS using GA in Multi-agent System for Solving Flexible Job Shop Problem . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 94-101. DOI: 10.5220/0005511000940101


in Bibtex Style

@conference{icinco15,
author={Ameni Azzouz and Meriem Ennigrou and Boutheina Jlifi},
title={Diversifying TS using GA in Multi-agent System for Solving Flexible Job Shop Problem},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={94-101},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005511000940101},
isbn={978-989-758-122-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Diversifying TS using GA in Multi-agent System for Solving Flexible Job Shop Problem
SN - 978-989-758-122-9
AU - Azzouz A.
AU - Ennigrou M.
AU - Jlifi B.
PY - 2015
SP - 94
EP - 101
DO - 10.5220/0005511000940101