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
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
收藏
页码:2592 / 2612
页数:21
相关论文
共 72 条
[61]   An effective differential evolution with level comparison for constrained engineering design [J].
Wang, Ling ;
Li, Ling-po .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2010, 41 (06) :947-963
[62]   Constrained optimization based on hybrid evolutionary algorithm and adaptive constraint-handling technique [J].
Wang, Yong ;
Cai, Zixing ;
Zhou, Yuren ;
Fan, Zhun .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2009, 37 (04) :395-413
[63]   Multiobjective optimization and hybrid evolutionary algorithm to solve constrained optimization problems [J].
Wang, Yong ;
Cai, Zixing ;
Guo, Guanqi ;
Zhou, Yuren .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2007, 37 (03) :560-575
[64]   A Dynamic Hybrid Framework for Constrained Evolutionary Optimization [J].
Wang, Yong ;
Cai, Zixing .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2012, 42 (01) :203-217
[65]   Combining Multiobjective Optimization with Differential Evolution to Solve Constrained Optimization Problems [J].
Wang, Yong ;
Cai, Zixing .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2012, 16 (01) :117-134
[66]   Constrained Evolutionary Optimization by Means of (μ plus λ)-Differential Evolution and Improved Adaptive Trade-Off Model [J].
Wang, Yong ;
Cai, Zixing .
EVOLUTIONARY COMPUTATION, 2011, 19 (02) :249-285
[67]   A hybrid multi-swarm particle swarm optimization to solve constrained optimization problems [J].
Wang, Yong ;
Cai, Zixing .
FRONTIERS OF COMPUTER SCIENCE IN CHINA, 2009, 3 (01) :38-52
[68]   Evolutionary algorithms, simulated annealing and tabu search: a comparative study [J].
Youssef, H ;
Sait, SM ;
Adiche, H .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2001, 14 (02) :167-181
[69]   A hybrid genetic algorithm for twice continuously differentiable NLP problems [J].
Yuan, Quan ;
Qian, Feng .
COMPUTERS & CHEMICAL ENGINEERING, 2010, 34 (01) :36-41
[70]   Hybrid Nelder-Mead simplex search and particle swarm optimization for constrained engineering design problems [J].
Zahara, Erwie ;
Kao, Yi-Tung .
EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (02) :3880-3886