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Memetic Algorithm for Solving the 0-1 Multidimensional Knapsack Problem

机译:解决0-1多维背包问题的膜算法

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In this paper, we propose a memetic algorithm for the Multidimensional Knapsack Problem (MKP). First, we propose to combine a genetic algorithm with a stochastic local search (GA-SLS), then with a simulated annealing (GA-SA). The two proposed versions of our approach (GA-SLS and GA-SA) are implemented and evaluated on bench-marks to measure their performance. The experiments show that both GA-SLS and GA-SA are able to find competitive results compared to other well-known hybrid GA based approaches.
机译:在本文中,我们提出了一种用于多维背包问题(MKP)的迭代算法。首先,我们建议将遗传算法与随机本地搜索(GA-SLS)组合,然后用模拟退火(GA-SA)。我们的方法(GA-SLS和GA-SA)的两个建议版本在基准标记上实施和评估,以衡量其性能。实验表明,与其他众所周知的混合GA的方法相比,GA-SLS和GA-SA都能够找到竞争结果。

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