A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice |
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| Affiliation: | 1. Materials and Construction Research Division, Building and Fire Research Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899-8611, USA;2. Department of Civil and Environmental Engineering, University of Maryland, College Park, MD 20742, USA;1. Department of Computer Science & Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul, 139-701, Republic of Korea;2. Department of Computer Engineering, Gachon University, 1342 Seongnamdaero, Sujeong-gu, Seongnam-si, Gyeonggi-do, 461-701, Republic of Korea;3. Department of Energy & Information Technology, Gachon University, 1342 SeongnamDaero, Sujeong-Gu, Seongman-Si, Gyeonggi-do, 461-701, Republic of Korea;1. State Key Lab of Digital Manufacturing Equipment & Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, China;2. Department of Electronics and Information Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, China;1. College of Computer Science & Technology, Zhejiang University of Technology, Hangzhou 310023, China;2. College of Field Engineering, PLA University of Science & Technology, Nanjing 210007, China;3. Jiangxi Provincial Lab of High-Performance Computing, Jiangxi Normal University, Nanchang 330022, China;1. Petroleum University of Technology, POB 6198144471, Ahwaz, Iran;2. Heriot-Watt University, Edinburgh, United Kingdom;1. School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou 510006, China;2. College of Information & Science, Northeastern University, Shenyang 110819, China;3. Graduate School of Business and Law, RMIT University, Melbourne 3000, Australia;4. School of Electrical Engineering and Automation, Xuzhou Normal University, Xuzhou 221116, China |
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| Abstract: | Most engineering optimization algorithms are based on numerical linear and nonlinear programming methods that require substantial gradient information and usually seek to improve the solution in the neighborhood of a starting point. These algorithms, however, reveal a limited approach to complicated real-world optimization problems. If there is more than one local optimum in the problem, the result may depend on the selection of an initial point, and the obtained optimal solution may not necessarily be the global optimum. This paper describes a new harmony search (HS) meta-heuristic algorithm-based approach for engineering optimization problems with continuous design variables. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. Various engineering optimization problems, including mathematical function minimization and structural engineering optimization problems, are presented to demonstrate the effectiveness and robustness of the HS algorithm. The results indicate that the proposed approach is a powerful search and optimization technique that may yield better solutions to engineering problems than those obtained using current algorithms. |
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