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

被引：745

作者：

Sadollah, Ali ^{[1
]}

Bahreininejad, Ardeshir ^{[1
]}

Eskandar, Hadi ^{[2
]}

Hamdi, Mohd ^{[1
]}

机构：

[1] Univ Malaya, Fac Engn, Kuala Lumpur 50603, Malaysia

[2] Semnan Univ, Fac Engn, Semnan, Iran

来源：

APPLIED SOFT COMPUTING | 2013年 / 13卷 / 05期

关键词：

Mine blast algorithm; Metaheuristic; Constrained optimization; Engineering design problems; Constraint handling; Global optimization; PARTICLE SWARM OPTIMIZATION; HYBRID EVOLUTIONARY ALGORITHM; DIFFERENTIAL EVOLUTION; GENETIC ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION; DESIGN OPTIMIZATION; SEARCH;

D O I：

10.1016/j.asoc.2012.11.026

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2012 Elsevier B. V. All rights reserved.

引用

页码：2592 / 2612

页数：21