Combining Tabu Search and Genetic Algorithm in a Multi-agent System for Solving Flexible Job Shop Problem

Author

Azzouz, Ameni ; Ennigrou, Meriem ; Jlifi, Boutheina ; Ghédira, Khaléd

Author_Institution

Strategies d´´Optimization des Informations et de la ConnaissancE, Inst. Super. de Gestion, Le Bardo, Tunisia

fYear

2012

fDate

Oct. 27 2012-Nov. 4 2012

Firstpage

83

Lastpage

88

Abstract

The Flexible Job Shop problem (FJSP) is an important extension of the classical job shop scheduling problem, in that each operation can be processed by a set of resources and has a processing time depending on the resource used. The objective is to minimize the make span, i.e., the time needed to complete all the jobs. This works aims to propose a new promising approach using multi-agent systems in order to solve the FJSP. Our model combines a local optimization approach based on Tabu Search (TS) meta-heuristic and a global optimization approach based on genetic algorithm (GA).

Keywords

genetic algorithms; job shop scheduling; multi-agent systems; search problems; FJSP; flexible job shop problem solving; genetic algorithm; global optimization approach; job shop scheduling problem; local optimization approach; meta-heuristic; multiagent system; tabu search; Biological cells; Dynamic scheduling; Genetic algorithms; Multiagent systems; Optimization; Sociology; Statistics; Diversification; Flexible Job Shop; Genetic algorithm; Multi-Agent System; Tabu Search;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence (MICAI), 2012 11th Mexican International Conference on

Conference_Location

San Luis Potosi

Print_ISBN

978-1-4673-4731-0

Type

conf

DOI

10.1109/MICAI.2012.12

Filename

6387220