2012

Conférence

n International Conference on Enterprise Information Systems (Vol. 3, pp. 47-53)

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).

@inproceedings{azzouz2012combining,
  title={Combining tabu search and genetic algorithm in a multi-agent system for solving flexible job shop problem},
  author={Azzouz, Ameni and Ennigrou, Meriem and Jlifi, Boutheina and Gh{\'e}dira, Khal{\'e}d},
  booktitle={2012 11th Mexican International Conference on Artificial Intelligence},
  pages={83--88},
  year={2012},
  organization={IEEE}
}