Hybrid genetic algorithm for bi-objective assignment problem

Mustapha Ratli (1) , Mansour Eddaly (2) , Bassem Jarboui (2) , Sylvain Lecomte (1) , Said Hanafi (1)

1 LAMIH - Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201
2 Université de Sfax - University of Sfax

We propose a hybrid approach for multi-objective assignment problem which combines genetic algorithm and mathematical programming techniques. This method is based on the dominance cost variant of the multi-objective genetic algorithm hybridized with exact method. The initial population is generated by solving a series of mono-objective assignment problems obtained by a suitable choice of a set of weights. The crossover operator solves a reduced mono-objective problem where the weights are chosen to identify an unexplored region. Numerical experiments show the efficiency of our approach.

Domaines: Informatique [cs]

Mustapha Ratli, Mansour Eddaly, Bassem Jarboui, Sylvain Lecomte, Said Hanafi. Hybrid genetic algorithm for bi-objective assignment problem. International Conference on Industrial Engineering and Systems Management (IEEE-IESM'2013), Oct 2013, Rabat, Morocco. ⟨hal-03473054⟩