Lamarckian genetic algorithmsapplied to the aggregation of preferences

Irène Charon and Olivier Hudry

Annals of Operations Research, 1998, vol. 80, issue 0, 297 pages

Abstract: The problem that we deal with consists in aggregating a set of individual preferencesinto a collective linear order summarizing the initial set as accurately as possible. As thisproblem is NP-hard, we apply heuristics to find good approximate solutions. More precisely,we design a Lamarckian genetic algorithm by hybridizing some meta-heuristics (based onthe simulated annealing method or the noising method) with a genetic algorithm. For theproblems that we studied, the experiments show that such a hybridization brings improvementsto these already good methods. Copyright Kluwer Academic Publishers 1998

Date: 1998
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DOI: 10.1023/A:1018976217274

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