A parallel exact hybrid approach for solving multi- objective problems on the computational grid

Authors:
M. Mezmaz;N. Melab;E.-G. Talbi
Affiliations:
Laboratoire d'Informatique Fondamentale de Lille, UMR CNRS, INRIA Futurs, Villeneuve d'Ascq cedex, France;Laboratoire d'Informatique Fondamentale de Lille, UMR CNRS, INRIA Futurs, Villeneuve d'Ascq cedex, France;Laboratoire d'Informatique Fondamentale de Lille, UMR CNRS, INRIA Futurs, Villeneuve d'Ascq cedex, France
Venue:
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Year:
2006

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Abstract

This paper presents a parallel hybrid exact multiobjective approach which combines two metaheuristics - a genetic algorithm (GA) and a memetic algorithm (MA), with an exact method - a branch and bound (B&B) algorithm. Such approach profits from both the exploration power of the GA, the intensification capability of the MA and the ability of the B&B to provide optimal solutions with proof of optimality. To fully exploit the resources of a computational grid, the hybrid method is parallelized according to three wellknown parallel models - the island model for the GA, the multi-start model for the MA and the parallel tree exploration model for the B&B. The obtained method has been experimented and validated on a bi-objective flow-shop scheduling problem. The approach allowed to solve exactly for the first time an instance of the problem - 50 jobs on 5 machines. More than 400 processors belonging to 4 administrative domains have contributed to the resolution process during more than 6 days.