Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems

• Published in: Computer methods in applied mechanics and engineering Vol. 197; no. 33; pp. 3080 - 3091
• Main Authors: Fesanghary, M., Mahdavi, M., Minary-Jolandan, M., Alizadeh, Y.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.06.2008; Elsevier
• Subjects: Applied sciences; Engineering optimization; Exact sciences and technology; Flows in networks. Combinatorial problems; Harmony search algorithm; Heuristic; Hybridization; Mechanical engineering. Machine design; Operational research and scientific management; Operational research. Management science; Sequential quadratic programming; Hybridization; Sequential quadratic programming; Engineering optimization; Heuristic; Harmony search algorithm; Local search; Empirical method; Combinatorial optimization; Quadratic programming; Modeling; Search algorithm; Convergence; Engineering design; Sequential method; Heuristic method; Hybrid model; Robustness; Deterministic approach; Metamodel
• ISSN: 0045-7825; 1879-2138
• DOI: 10.1016/j.cma.2008.02.006

This study presents a hybrid harmony search algorithm (HHSA) to solve engineering optimization problems with continuous design variables. Although the harmony search algorithm (HSA) has proven its ability of finding near global regions within a reasonable time, it is comparatively inefficient in performing local search. In this study sequential quadratic programming (SQP) is employed to speed up local search and improve precision of the HSA solutions. Moreover, an empirical study is performed in order to determine the impact of various parameters of the HSA on convergence behavior. Various benchmark engineering optimization problems are used to illustrate the effectiveness and robustness of the proposed algorithm. Numerical results reveal that the proposed hybrid algorithm, in most cases is more effective than the HSA and other meta-heuristic or deterministic methods.