文件名称:ACO-TSP
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Ant Colony Optimization Algorithm (ACO) and TSP
ACO algorithm mimics the behavior of real life ants and on how they interact with each other. The basic philosophy of the algorithm involves the movement of a colony of ants through the different states of the problem influenced by two local decision policies, viz., trails and attractiveness and two mechanisms, viz., trail evaporation and daemon actions. The algorithm aims to search for an optimal path based on the behavior of ants seeking a path between their colony and a source of food. Thereby, each such ant incrementally constructs a solution to the problem.
ACO algorithm mimics the behavior of real life ants and on how they interact with each other. The basic philosophy of the algorithm involves the movement of a colony of ants through the different states of the problem influenced by two local decision policies, viz., trails and attractiveness and two mechanisms, viz., trail evaporation and daemon actions. The algorithm aims to search for an optimal path based on the behavior of ants seeking a path between their colony and a source of food. Thereby, each such ant incrementally constructs a solution to the problem.
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下载文件列表
ACO-TSP/ACO.m
ACO-TSP/ACO_Elitist.m
ACO-TSP/ACO_rank.m
ACO-TSP/ACS.m
ACO-TSP/calculated_distance.m
ACO-TSP/data.xlsx
ACO-TSP/fitness.m
ACO-TSP/MMAS.m
ACO-TSP/RouletteWheel.m
ACO-TSP/~$data.xlsx
ACO-TSP
ACO-TSP/ACO_Elitist.m
ACO-TSP/ACO_rank.m
ACO-TSP/ACS.m
ACO-TSP/calculated_distance.m
ACO-TSP/data.xlsx
ACO-TSP/fitness.m
ACO-TSP/MMAS.m
ACO-TSP/RouletteWheel.m
ACO-TSP/~$data.xlsx
ACO-TSP
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