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Lamarckian genetic algorithmsapplied to the aggregation of preferences

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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.

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Charon, I., Hudry, O. Lamarckian genetic algorithmsapplied to the aggregation of preferences. Annals of Operations Research 80, 281–297 (1998). https://doi.org/10.1023/A:1018976217274

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