基于对立的鲸鱼优化算法求解0/1背包问题

Hammoudeh S. Alamri, K. Z. Zamli, M. Razak, Ahmad Firdaus
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引用次数: 2

摘要

0/1背包问题是现实世界中最常见的搜索空间和寻找最优解的优化问题之一。理论上,0/1背包的最优解问题需要合适的技术来有效地探索搜索空间。实际上,与许多元启发式算法一样,鲸鱼优化算法(Whale Optimization Algorithm, WOA)可能在局部最优解中失败。本文提出了基于对立的鲸鱼优化算法(OWOA)来优化0/1背包中的求解问题。OWOA对原始WOA进行了测试,使用了20例背包问题,并与其他元启发式算法(CGMA)和HS-Jaya进行了比较。实验结果表明,该优化方案具有较好的稳定性,且具有最小标准差值。这表明该算法改进了原始版本的WOA,并且与其他现有算法相比具有良好的效果。
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Solving 0/1 Knapsack Problem using Opposition-based Whale Optimization Algorithm (OWOA)
The 0/1 Knapsack problem is one of the most popular real-world optimization problems that arise in searching space and finding the most optimum solution. Theoretically, the optimum solution problem of the 0/1 Knapsack requires suitable technique to explore the search space effectively. Practically, as many metaheuristic algorithms, Whale Optimization Algorithm (WOA) may fail in local optimum solution. This paper proposes Opposition-based Whale Optimization Algorithm (OWOA) to optimize solution problem in 0/1 Knapsack. The OWOA has been tested original WOA by using twenty cases of Knapsack problem and against other metaheuristic algorithms such as (CGMA) and HS-Jaya. The experimental results indicate a significant performance of the optimization solution and stabilization with minimal standard deviation value. This shows that the OWOA improved the original version WOA and has promising result in comparison with other existing algorithms.
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