Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems

• Published in: Applied soft computing Vol. 13; no. 5; pp. 2592 - 2612
• Main Authors: Sadollah, Ali, Bahreininejad, Ardeshir, Eskandar, Hadi, Hamdi, Mohd
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2013
• Subjects: Constrained optimization; Constraint handling; Engineering design problems; Global optimization; Metaheuristic; Mine blast algorithm; Constraint handling; Metaheuristic; Global optimization; Engineering design problems; Mine blast algorithm; Constrained optimization
• ISSN: 1568-4946; 1872-9681
• DOI: 10.1016/j.asoc.2012.11.026

[Display omitted] ► A novel optimization algorithm called the mine blast algorithm (MBA). ► MBA with embedded constraint handling methods is proposed. ► MBA outperforms numerous metaheuristic methods in terms of solutions and convergence. ► The function values are reduced to near optimum solution in the early iterations. A novel population-based algorithm based on the mine bomb explosion concept, called the mine blast algorithm (MBA), is applied to the constrained optimization and engineering design problems. A comprehensive comparative study has been carried out to show the performance of the MBA over other recognized optimizers in terms of computational effort (measured as the number of function evaluations) and function value (accuracy). Sixteen constrained benchmark and engineering design problems have been solved and the obtained results were compared with other well-known optimizers. The obtained results demonstrate that, the proposed MBA requires less number of function evaluations and in most cases gives better results compared to other considered algorithms.