A Comparison between Genetic Algorithm and k-opt local search method for the Vehicle Routing Problem
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概要
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The Traveling Salesman problem (TSP) can be used to method many practical problems. The Vehicle Routing Problem (VRP) is more complicated than TSP because it requires determinig which customers are assigned to each vehicles, as well as the optimal ordering of the cities within each vehcle's tour. Previous studies proposed that Genetic Algorithm, Integer Programming and several neural network approaches could be used to solve VRP. This paper compared the results for Genetic Algorithm (GA) as a Meta-Heuristic method and k-opt local search method as a heuristic method. We proposed three VRP-cases for simulations. Then, each case is solved with k-opt and GA in terms of performance and computing time.
著者
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韓 尚憲
Nagoya University of Commerce and Business
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韓 尚憲
名古屋商科大学
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Han Sangheon
Nagoya Univ. Commerce & Business Aichi‐ken Jpn
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