A Hybrid Genetic-Hierarchical Algorithm for the Quadratic Assignment Problem |
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Authors: | Alfonsas Misevi
ius Dovil Veren |
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Institution: | Department of Multimedia Engineering, Kaunas University of Technology, Studentu st. 50-400/416a, LT-51368 Kaunas, Lithuania; |
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Abstract: | In this paper, we present a hybrid genetic-hierarchical algorithm for the solution of the quadratic assignment problem. The main distinguishing aspect of the proposed algorithm is that this is an innovative hybrid genetic algorithm with the original, hierarchical architecture. In particular, the genetic algorithm is combined with the so-called hierarchical (self-similar) iterated tabu search algorithm, which serves as a powerful local optimizer (local improvement algorithm) of the offspring solutions produced by the crossover operator of the genetic algorithm. The results of the conducted computational experiments demonstrate the promising performance and competitiveness of the proposed algorithm. |
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Keywords: | combinatorial optimization hybrid heuristic algorithms hierarchical heuristic algorithms genetic algorithms tabu search quadratic assignment problem |
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