Use of a genetic heritage for solving the assignment problem with two objectives

Authors:
Xavier Gandibleux;Hiroyuki Morita;Naoki Katoh
Affiliations:
LAMIH/ROI, UMR CNRS, Université de Valenciennes, Valenciennes, France;Osaka Prefecture University, Sakai, Osaka, Japan;Kyoto University, Kyoto, Japan
Venue:
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Year:
2003

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Abstract

The paper concerns a multiobjective heuristic to compute approximate efficient solutions for the assignment problem with two objectives. The aim here is to show that the genetic information extracted from supported solutions constitutes a useful genetic heritage to be used by crossover operators to approximate non-supported solutions. Bound sets describe one acceptable limit for applying a local search over an offspring. Results of extensive numerical experiments are reported. All exact efficient solutions are obtained using Cplex in a basic enumerative procedure. A comparison with published results shows the efficiency of this approach.