An effective hybrid cuckoo search algorithm for constrained global optimization

Abstract As a novel evolutionary computation, cuckoo search (CS) algorithm has attracted much attention and wide applications, owing to its easy implementation. CS as most population-based algorithm is good at identifying promising area of the search space, but less good at fine-tuning the approximation to the minimization. To the best of our knowledge, the hybridization of augmented Lagrangian method, cuckoo search and Solis and Wets local search has not been attempted yet. In this paper, an effective hybrid cuckoo search algorithm based on Solis and Wets local search technique is proposed for constrained global optimization that relies on an augmented Lagrangian function for constraint-handling. Numerical results and comparisons with other state-of-the-art stochastic algorithms using a set of benchmark constrained test functions and engineering design optimization problems are provided.

[1]  Tapabrata Ray,et al.  A socio-behavioural simulation model for engineering design optimization , 2002 .

[2]  Xin-She Yang,et al.  Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[3]  Ardeshir Bahreininejad,et al.  Water cycle algorithm - A novel metaheuristic optimization method for solving constrained engineering optimization problems , 2012 .

[4]  Roger J.-B. Wets,et al.  Minimization by Random Search Techniques , 1981, Math. Oper. Res..

[5]  Xin Yao,et al.  Stochastic ranking for constrained evolutionary optimization , 2000, IEEE Trans. Evol. Comput..

[6]  Yin Ming-hao,et al.  Parameter estimation for chaotic systems using the cuckoo search algorithm with an orthogonal learning method , 2012 .

[7]  Zhun Fan,et al.  Constrained optimization based on hybrid evolutionary algorithm and adaptive constraint-handling technique , 2009 .

[8]  Ruben E. Perez,et al.  Constrained structural design optimization via a parallel augmented Lagrangian particle swarm optimization approach , 2011 .

[9]  Carlos A. Coello Coello,et al.  THEORETICAL AND NUMERICAL CONSTRAINT-HANDLING TECHNIQUES USED WITH EVOLUTIONARY ALGORITHMS: A SURVEY OF THE STATE OF THE ART , 2002 .

[10]  Amir Hossein Gandomi,et al.  Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems , 2011, Engineering with Computers.

[11]  Tapabrata Ray,et al.  ENGINEERING DESIGN OPTIMIZATION USING A SWARM WITH AN INTELLIGENT INFORMATION SHARING AMONG INDIVIDUALS , 2001 .

[12]  Amir Hossein Gandomi,et al.  Bat algorithm for constrained optimization tasks , 2012, Neural Computing and Applications.

[13]  Hitoshi Iba,et al.  Accelerating Differential Evolution Using an Adaptive Local Search , 2008, IEEE Transactions on Evolutionary Computation.

[14]  Carlos A. Coello Coello,et al.  Engineering optimization using simple evolutionary algorithm , 2003, Proceedings. 15th IEEE International Conference on Tools with Artificial Intelligence.

[15]  Yafei Huang,et al.  A hybrid differential evolution augmented Lagrangian method for constrained numerical and engineering optimization , 2013, Comput. Aided Des..

[16]  Anthony Chen,et al.  Constraint handling in genetic algorithms using a gradient-based repair method , 2006, Comput. Oper. Res..

[17]  X. Q. Yang,et al.  Augmented Lagrangian functions for constrained optimization problems , 2012, J. Glob. Optim..

[18]  Ashok Dhondu Belegundu,et al.  A Study of Mathematical Programming Methods for Structural Optimization , 1985 .

[19]  José Mario Martínez,et al.  Augmented Lagrangian method with nonmonotone penalty parameters for constrained optimization , 2011, Computational Optimization and Applications.

[20]  Erwie Zahara,et al.  Hybrid Nelder-Mead simplex search and particle swarm optimization for constrained engineering design problems , 2009, Expert Syst. Appl..

[21]  Reza Tavakkoli-Moghaddam,et al.  A novel hybrid approach combining electromagnetism-like method with Solis and Wets local search for continuous optimization problems , 2009, J. Glob. Optim..

[22]  Leandro dos Santos Coelho,et al.  Coevolutionary Particle Swarm Optimization Using Gaussian Distribution for Solving Constrained Optimization Problems , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[23]  Min-Jea Tahk,et al.  Coevolutionary augmented Lagrangian methods for constrained optimization , 2000, IEEE Trans. Evol. Comput..

[24]  H Nowacki,et al.  OPTIMIZATION IN PRE-CONTRACT SHIP DESIGN , 1973 .

[25]  Carlos A. Coello Coello,et al.  A simple multimembered evolution strategy to solve constrained optimization problems , 2005, IEEE Transactions on Evolutionary Computation.

[26]  Jianbo Hu,et al.  A Modified Augmented Lagrange Multiplier Method for Large-Scale Optimization , 2008 .

[27]  M. M. Ali,et al.  An electromagnetism-like method for nonlinearly constrained global optimization , 2010, Comput. Math. Appl..

[28]  Efrén Mezura-Montes,et al.  Empirical analysis of a modified Artificial Bee Colony for constrained numerical optimization , 2012, Appl. Math. Comput..

[29]  Patrick Siarry,et al.  Biogeography-based optimization for constrained optimization problems , 2012, Comput. Oper. Res..

[30]  Carlos A. Coello Coello,et al.  Useful Infeasible Solutions in Engineering Optimization with Evolutionary Algorithms , 2005, MICAI.

[31]  N. Hansen,et al.  Markov Chain Analysis of Cumulative Step-Size Adaptation on a Linear Constrained Problem , 2015, Evolutionary Computation.

[32]  M. Mahdavi,et al.  ARTICLE IN PRESS Available online at www.sciencedirect.com , 2007 .

[33]  Haiyan Lu,et al.  Self-adaptive velocity particle swarm optimization for solving constrained optimization problems , 2008, J. Glob. Optim..

[34]  Amir Hossein Alavi,et al.  Krill herd: A new bio-inspired optimization algorithm , 2012 .

[35]  Sankha Deb,et al.  Scheduling optimization of flexible manufacturing system using cuckoo search-based approach , 2013 .

[36]  Ana Maria A. C. Rocha,et al.  An augmented Lagrangian fish swarm based method for global optimization , 2011, J. Comput. Appl. Math..

[37]  Wenjian Luo,et al.  Differential evolution with dynamic stochastic selection for constrained optimization , 2008, Inf. Sci..

[38]  Yong Wang,et al.  Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization , 2010, Appl. Soft Comput..

[39]  Lino A. Costa,et al.  A hybrid genetic pattern search augmented Lagrangian method for constrained global optimization , 2012, Appl. Math. Comput..

[40]  Ling Wang,et al.  An effective co-evolutionary differential evolution for constrained optimization , 2007, Appl. Math. Comput..

[41]  E. Sandgren,et al.  Nonlinear Integer and Discrete Programming in Mechanical Design Optimization , 1990 .

[42]  A. Gandomi,et al.  Mixed variable structural optimization using Firefly Algorithm , 2011 .

[43]  Carlos A. Coello Coello,et al.  Constraint-handling in genetic algorithms through the use of dominance-based tournament selection , 2002, Adv. Eng. Informatics.