Toufik Mzili, Ilyass Mzili, Mohammed Essaid Riffi, Dragan Pamucar, Vladimir Simic, Mohamed Kurdi
{"title":"A NOVEL DISCRETE RAT SWARM OPTIMIZATION ALGORITHM FOR THE QUADRATIC ASSIGNMENT PROBLEM","authors":"Toufik Mzili, Ilyass Mzili, Mohammed Essaid Riffi, Dragan Pamucar, Vladimir Simic, Mohamed Kurdi","doi":"10.22190/fume230602024m","DOIUrl":null,"url":null,"abstract":"The quadratic assignment problem (QAP) is an NP-hard problem with a wide range of applications in many real-world applications. This study introduces a discrete rat swarm optimizer (DRSO)algorithm for the first time as a solution to the QAP and demonstrates its effectiveness in terms of solution quality and computational efficiency. To address the combinatorial nature of the QAP, a mapping strategy is introduced to convert real values into discrete values, and mathematical operators are redefined to make then suitable for combinatorial problems. Additionally, a solution quality improvement strategy based on local search heuristics such as 2-opt and 3-opt is proposed. Simulations with test instances from the QAPLIB test library validate the effectiveness of the DRSO algorithm, and statistical analysis using the Wilcoxon parametric test confirms its performance. Comparative analysis with other algorithms demonstrates the superior performance of DRSO in terms of solution quality, convergence speed, and deviation from the best-known values, making it a promising approach for solving the QAP.","PeriodicalId":51338,"journal":{"name":"Facta Universitatis-Series Mechanical Engineering","volume":"503 ","pages":"0"},"PeriodicalIF":10.1000,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Facta Universitatis-Series Mechanical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22190/fume230602024m","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The quadratic assignment problem (QAP) is an NP-hard problem with a wide range of applications in many real-world applications. This study introduces a discrete rat swarm optimizer (DRSO)algorithm for the first time as a solution to the QAP and demonstrates its effectiveness in terms of solution quality and computational efficiency. To address the combinatorial nature of the QAP, a mapping strategy is introduced to convert real values into discrete values, and mathematical operators are redefined to make then suitable for combinatorial problems. Additionally, a solution quality improvement strategy based on local search heuristics such as 2-opt and 3-opt is proposed. Simulations with test instances from the QAPLIB test library validate the effectiveness of the DRSO algorithm, and statistical analysis using the Wilcoxon parametric test confirms its performance. Comparative analysis with other algorithms demonstrates the superior performance of DRSO in terms of solution quality, convergence speed, and deviation from the best-known values, making it a promising approach for solving the QAP.
二次分配问题(QAP)是一个np困难问题,在许多实际应用中有着广泛的应用。本文首次引入离散鼠群优化算法(discrete rat swarm optimizer, DRSO)作为QAP的解决方案,并从求解质量和计算效率两方面证明了该算法的有效性。为了解决QAP的组合特性,引入了映射策略将实值转换为离散值,并重新定义了数学运算符,使其适合于组合问题。此外,提出了一种基于2-opt和3-opt局部搜索启发式的解质量改进策略。利用QAPLIB测试库中的测试实例进行仿真,验证了DRSO算法的有效性,并使用Wilcoxon参数检验进行统计分析,证实了其性能。与其他算法的比较分析表明,DRSO在解质量、收敛速度和与已知值的偏差方面具有优越的性能,使其成为求解QAP的一种有前途的方法。
期刊介绍:
Facta Universitatis, Series: Mechanical Engineering (FU Mech Eng) is an open-access, peer-reviewed international journal published by the University of Niš in the Republic of Serbia. It publishes high-quality, refereed papers three times a year, encompassing original theoretical and/or practice-oriented research as well as extended versions of previously published conference papers. The journal's scope covers the entire spectrum of Mechanical Engineering. Papers undergo rigorous peer review to ensure originality, relevance, and readability, maintaining high publication standards while offering a timely, comprehensive, and balanced review process.