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引用次数: 14

摘要

本文提出了一种新的基于蚁群隐喻的优化算法和一种求解多背包问题的新方法。MKP问题是将n个物品的子集分配给m个不同的背包,使所选物品的总利润最大化,而不超过每个背包的容量。该问题在自适应以及MKP解的轨迹表示或该方法中应用的动态变化的启发式函数方面存在一些困难。给出的结果显示了蚁群算法解决这类子集问题的能力。
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Ants and Multiple Knapsack Problem
In this paper a new optimization algorithm based on ant colony metaphor (ACO)and a new approach for the Multiple Knapsack Problem is presented. The MKP is the problem of assigning a subset of n items to m distinct knapsacks, such that the total profit sum of the selected items is maximized, without exceeding the capacity of each of the knapsacks. The problem has several difficulties in adaptation as well as the trail representation of the solutions of MKP or a dynamically changed heuristic function applied in this approach. Presented results show the power of the ACO approach for solving this type of subset problems.
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