{"title":"使用基于粒子群优化器和 Harris Hawk 算法的混合方法优化桁架设计","authors":"M. Yassami","doi":"10.14525/jjce.v18i1.07","DOIUrl":null,"url":null,"abstract":"This paper presents two hybrid optimization methods known as PSOHHO and DPSOHHO optimization algorithms. In the first method, using a number of formulae, the top populations are exchanged between the two algorithms and a new population is created and in the second method, we adopted the parallel optimization and optimized its performance. In this method, unlike other parallel methods, the population does not remain constant. With this ability, the strengths of an algorithm can be used to compensate for the weaknesses of the other algorithm. In these methods, no changes are made to the algorithms. The main goal is to use existing algorithms. These methods attain the optimal solution in the shortest time possible. Two algorithms of particleswarm optimization (PSO) and Harris Hawks's optimization (HHO) are used to present this method and two truss samples and CEC209 are considered to confirm the performance of this method. Based on the results, these methods have rapid convergence speed and acceptable results compared to other methods. KEYWORDS: Meta-heuristic algorithms, Hybrid algorithm, Optimization, Dynamic hybrid algorithm, Truss.","PeriodicalId":51814,"journal":{"name":"Jordan Journal of Civil Engineering","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Design of Truss Using a Hybrid Method Based on Particle Swarm Optimizer and Harris Hawk Algorithm\",\"authors\":\"M. Yassami\",\"doi\":\"10.14525/jjce.v18i1.07\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents two hybrid optimization methods known as PSOHHO and DPSOHHO optimization algorithms. In the first method, using a number of formulae, the top populations are exchanged between the two algorithms and a new population is created and in the second method, we adopted the parallel optimization and optimized its performance. In this method, unlike other parallel methods, the population does not remain constant. With this ability, the strengths of an algorithm can be used to compensate for the weaknesses of the other algorithm. In these methods, no changes are made to the algorithms. The main goal is to use existing algorithms. These methods attain the optimal solution in the shortest time possible. Two algorithms of particleswarm optimization (PSO) and Harris Hawks's optimization (HHO) are used to present this method and two truss samples and CEC209 are considered to confirm the performance of this method. Based on the results, these methods have rapid convergence speed and acceptable results compared to other methods. KEYWORDS: Meta-heuristic algorithms, Hybrid algorithm, Optimization, Dynamic hybrid algorithm, Truss.\",\"PeriodicalId\":51814,\"journal\":{\"name\":\"Jordan Journal of Civil Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jordan Journal of Civil Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14525/jjce.v18i1.07\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jordan Journal of Civil Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14525/jjce.v18i1.07","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Optimal Design of Truss Using a Hybrid Method Based on Particle Swarm Optimizer and Harris Hawk Algorithm
This paper presents two hybrid optimization methods known as PSOHHO and DPSOHHO optimization algorithms. In the first method, using a number of formulae, the top populations are exchanged between the two algorithms and a new population is created and in the second method, we adopted the parallel optimization and optimized its performance. In this method, unlike other parallel methods, the population does not remain constant. With this ability, the strengths of an algorithm can be used to compensate for the weaknesses of the other algorithm. In these methods, no changes are made to the algorithms. The main goal is to use existing algorithms. These methods attain the optimal solution in the shortest time possible. Two algorithms of particleswarm optimization (PSO) and Harris Hawks's optimization (HHO) are used to present this method and two truss samples and CEC209 are considered to confirm the performance of this method. Based on the results, these methods have rapid convergence speed and acceptable results compared to other methods. KEYWORDS: Meta-heuristic algorithms, Hybrid algorithm, Optimization, Dynamic hybrid algorithm, Truss.
期刊介绍:
I am very pleased and honored to be appointed as an Editor-in-Chief of the Jordan Journal of Civil Engineering which enjoys an excellent reputation, both locally and internationally. Since development is the essence of life, I hope to continue developing this distinguished Journal, building on the effort of all the Editors-in-Chief and Editorial Board Members as well as Advisory Boards of the Journal since its establishment about a decade ago. I will do my best to focus on publishing high quality diverse articles and move forward in the indexing issue of the Journal.