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

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3 Author(s)
Mezmaz, M.-S. ; Lab. d'' Informatique Fondamentale de Lille, UMR CNRS, Villeneuve D'' Ascq ; Melab, N. ; Talbi, E.

This paper presents a parallel hybrid exact multi-objective 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 well-known 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

Published in:

Parallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International

Date of Conference:

25-29 April 2006

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