An effective binary dynamic grey wolf optimization algorithm for the 0-1 knapsack problem

IF 3 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Feyza Erdoğan, Murat Karakoyun, Şaban Gülcü
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Abstract

Metaheuristic algorithms are recommended and frequently used methods for solving optimization problems. Today, it has been adapted to many challenging problems and its successes have been identified. The grey wolf optimizer (GWO) is one of the most advanced metaheuristics. Because of the advantages it provides, GWO has been applied to solve many different problems. In this study, a new variant of GWO, the Binary Dynamic Grey Wolf Optimizer (BDGWO), is proposed for the solution of binary optimization problems. The main contributions of BDGWO compared to other binary GWO variants are that it uses the XOR bitwise operation to binarize and is based on the dynamic coefficient method developed to determine the effect of the three dominant wolves (alpha, beta, and delta) in the algorithm. BDGWO is a simple, feasible, and successful method that strikes a balance between local search and global search in solving binary optimization problems. To determine the success and accuracy of the proposed BDGWO, it was tested on the 0-1 knapsack problem (0-1 KP), which is classified as an NP-Hard problem. The BDGWO was compared with 17 different binary methods across a total of 55 data sets from three different studies published in the last four years. The Friedman test was applied to interpret the experimental results more easily and to evaluate the algorithm results statistically. As a result of the experiments, it has been proven that the BDGWO is an effective and successful method in accordance with its purpose.

Abstract Image

0-1 "knapsack "问题的有效二元动态灰狼优化算法
元启发式算法是解决优化问题的推荐和常用方法。如今,它已被应用于许多具有挑战性的问题,并取得了成功。灰狼优化器(GWO)是最先进的元启发式算法之一。由于它的优势,GWO 已被应用于解决许多不同的问题。本研究提出了 GWO 的一种新变体,即二元动态灰狼优化器(BDGWO),用于解决二元优化问题。与其他二进制 GWO 变体相比,BDGWO 的主要贡献在于它使用 XOR 位操作进行二进制化,并基于动态系数法来确定算法中三个主导灰狼(α、β 和 delta)的影响。BDGWO 是一种简单、可行且成功的方法,它在解决二进制优化问题时实现了局部搜索和全局搜索之间的平衡。为了确定所提出的 BDGWO 的成功率和准确性,我们在 0-1 Knapsack 问题(0-1 KP)上对其进行了测试,该问题被归类为 NP-Hard 问题。BDGWO 与 17 种不同的二进制方法进行了比较,共涉及 55 个数据集,这些数据集来自过去四年中发表的三项不同研究。为了更容易解释实验结果,并对算法结果进行统计评估,采用了弗里德曼检验法。实验结果证明,BDGWO 是一种有效且成功的方法,符合其目的。
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来源期刊
Multimedia Tools and Applications
Multimedia Tools and Applications 工程技术-工程:电子与电气
CiteScore
7.20
自引率
16.70%
发文量
2439
审稿时长
9.2 months
期刊介绍: Multimedia Tools and Applications publishes original research articles on multimedia development and system support tools as well as case studies of multimedia applications. It also features experimental and survey articles. The journal is intended for academics, practitioners, scientists and engineers who are involved in multimedia system research, design and applications. All papers are peer reviewed. Specific areas of interest include: - Multimedia Tools: - Multimedia Applications: - Prototype multimedia systems and platforms
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