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- W2893166012 abstract "In this paper, we propose an improved hybrid genetic algorithm for the solution of the grey pattern quadratic assignment problem (GP-QAP). The novelty is the hybridization of the genetic algorithm with the so-called hierarchical iterated tabu search algorithm. Very fast exploration of the neighbouring solutions within the tabu search algorithm is used. In addition, a smart combination of the tabu search and adaptive perturbations is adopted, which enables a good balance between diversification and intensification during the iterative optimization process. The results from the experiments with the GP-QAP instances show that our algorithm is superior to other heuristic algorithms. Many best known solutions have been discovered for the large-scaled GP-QAP instances. DOI: http://dx.doi.org/10.5755/j01.itc.47.3.20728" @default.
- W2893166012 created "2018-10-05" @default.
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- W2893166012 date "2018-09-26" @default.
- W2893166012 modified "2023-10-01" @default.
- W2893166012 title "A NEW HYBRID GENETIC ALGORITHM FOR THE GREY PATTERN QUADRATIC ASSIGNMENT PROBLEM" @default.
- W2893166012 doi "https://doi.org/10.5755/j01.itc.47.3.20728" @default.
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