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首页> 外文期刊>International journal of geotechnical earthquake engineering >A DIMMA-Based Memetic Algorithm for 0-1 Multidimensional Knapsack Problem Using DOE Approach for Parameter Tuning
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A DIMMA-Based Memetic Algorithm for 0-1 Multidimensional Knapsack Problem Using DOE Approach for Parameter Tuning

机译：基于DOA方法的0-1多维背包问题的基于DIMMA的模因算法

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摘要

Multidimensional 0-1 Knapsack Problem (MKP) is a well-known integer programming problems. The objective of MKP is to find a subset of items with maximum value satisfying the capacity constraints. A Memetic algorithm on the basis of Design and Implementation Methodology for Metaheuristic Algorithms (DIMMA) is proposed to solve MKP. DIMMA is a new methodology to develop a metaheuristic algorithm. The Memetic algorithm is categorized as metaheuristics and is a particular class of evolutionary algorithms. The parameters of the proposed algorithm are tuned by Design of Experiments (DOE) approach. DOE refers to the process of planning the experiment so that appropriate data that can be analyzed by statistical methods will be collected, resulting in valid and objective conclusions. The proposed algorithm is tested on several MKP standard instances from OR-Library. The results show the efficiency and effectiveness of the proposedalgorithm.
机译：多维0-1背包问题（MKP）是众所周知的整数编程问题。 MKP的目标是找到最大值满足容量约束的项目子集。提出了一种基于元启发式算法设计与实现方法的Memetic算法来解决MKP问题。 DIMMA是开发元启发式算法的新方法。 Memetic算法被归类为元启发式算法，并且是一类特殊的进化算法。通过实验设计（DOE）方法对所提出算法的参数进行了调整。 DOE是指计划实验的过程，以便收集可以通过统计方法分析的适当数据，从而得出有效和客观的结论。该算法在OR-Library的多个MKP标准实例上进行了测试。结果表明了该算法的有效性和有效性。

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