A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice

• Published in: Computer methods in applied mechanics and engineering Vol. 194; no. 36; pp. 3902 - 3933
• Main Authors: Lee, Kang Seok, Geem, Zong Woo
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.09.2005; Elsevier
• Subjects: Continuous design variables; Exact sciences and technology; Fundamental areas of phenomenology (including applications); Harmony search; Heuristic algorithm; Mathematical function minimization; Physics; Solid mechanics; Static elasticity (thermoelasticity...); Structural and continuum mechanics; Structural engineering optimization; Structural engineering optimization; Harmony search; Continuous design variables; Heuristic algorithm; Mathematical function minimization; Probabilistic approach; Global optimum; Linear programming; Non linear programming; Modeling; Optimization; Search algorithm; Design process; Function minimization; Heuristic method; Gradient method; Structural analysis
• ISSN: 0045-7825; 1879-2138
• DOI: 10.1016/j.cma.2004.09.007

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.