By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Ameni Azzouz ; Strategies d'Optimization des Informations et de la ConnaissancE, Inst. Super. de Gestion, Le Bardo, Tunisia ; Meriem Ennigrou ; Boutheina Jlifi ; Khaléd Ghédira

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).

Published in:

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

Date of Conference:

Oct. 27 2012-Nov. 4 2012