Some guidelines for genetic algorithms with penalty functions
Proceedings of the third international conference on Genetic algorithms
Use of a self-adaptive penalty approach for engineering optimization problems
Computers in Industry
Particle swarm optimization method in multiobjective problems
Proceedings of the 2002 ACM symposium on Applied computing
Stochastic ranking for constrained evolutionary optimization
IEEE Transactions on Evolutionary Computation
A simple multimembered evolution strategy to solve constrained optimization problems
IEEE Transactions on Evolutionary Computation
Differential evolution strategy for structural system identification
Computers and Structures
Expert Systems with Applications: An International Journal
Real-time deterministic chaos control by means of selected evolutionary techniques
Engineering Applications of Artificial Intelligence
A Novel Particle Swarm Optimization for Constrained Engineering Optimization Problems
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Computers & Mathematics with Applications
Particle swarm optimization: Tabu search approach to constrained engineering optimization problems
WSEAS Transactions on Mathematics
Heuristic Kalman algorithm for solving optimization problems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Knowledge and Information Systems
A theoretical and empirical analysis of convergence related particle swarm optimization
WSEAS Transactions on Systems and Control
A new heuristic approach for non-convex optimization problems
Information Sciences: an International Journal
Differential evolution with level comparison for constrained optimization
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Differential genetic particle swarm optimization for continuous function optimization
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Expert Systems with Applications: An International Journal
Using cooperative particle swarm for optimizing the engineering design problems
ACE'10 Proceedings of the 9th WSEAS international conference on Applications of computer engineering
Using CPSO for the engineering optimization problems
WSEAS Transactions on Mathematics
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Computers and Operations Research
A hybrid cooperative search algorithm for constrained optimization
Structural and Multidisciplinary Optimization
An improved vector particle swarm optimization for constrained optimization problems
Information Sciences: an International Journal
Hybrid optimization with improved tabu search
Applied Soft Computing
Expert Systems with Applications: An International Journal
An empirical analysis of convergence related particle swarm optimization
MMACTEE'09 Proceedings of the 11th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
Using CPSO for the engineering optimization problems
ICCOMP'10 Proceedings of the 14th WSEAS international conference on Computers: part of the 14th WSEAS CSCC multiconference - Volume II
PSO-GPU: accelerating particle swarm optimization in CUDA-based graphics processing units
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Engineering Applications of Artificial Intelligence
Expert Systems with Applications: An International Journal
Evaluating differential evolution with penalty function to solve constrained engineering problems
Expert Systems with Applications: An International Journal
Constrained optimization based on modified differential evolution algorithm
Information Sciences: an International Journal
Chaotic particle swarm optimization for data clustering
Expert Systems with Applications: An International Journal
International Journal of Bio-Inspired Computation
Engineering Applications of Artificial Intelligence
Comparison of evolutionary-based optimization algorithms for structural design optimization
Engineering Applications of Artificial Intelligence
A particle swarm-BFGS algorithm for nonlinear programming problems
Computers and Operations Research
Artificial cooperative search algorithm for numerical optimization problems
Information Sciences: an International Journal
Investigating Multi-View Differential Evolution for solving constrained engineering design problems
Expert Systems with Applications: An International Journal
Particle swarm optimization for solving engineering problems: A new constraint-handling mechanism
Engineering Applications of Artificial Intelligence
Three improved hybrid metaheuristic algorithms for engineering design optimization
Applied Soft Computing
A survey on optimization metaheuristics
Information Sciences: an International Journal
International Journal of Metaheuristics
International Journal of Bio-Inspired Computation
Review: Structural design employing a sequential approximation optimization approach
Computers and Structures
Advances in Engineering Software
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Many engineering design problems can be formulated as constrained optimization problems. So far, penalty function methods have been the most popular methods for constrained optimization due to their simplicity and easy implementation. However, it is often not easy to set suitable penalty factors or to design adaptive mechanism. By employing the notion of co-evolution to adapt penalty factors, this paper proposes a co-evolutionary particle swarm optimization approach (CPSO) for constrained optimization problems, where PSO is applied with two kinds of swarms for evolutionary exploration and exploitation in spaces of both solutions and penalty factors. The proposed CPSO is population based and easy to implement in parallel. Especially, penalty factors also evolve using PSO in a self-tuning way. Simulation results based on well-known constrained engineering design problems demonstrate the effectiveness, efficiency and robustness on initial populations of the proposed method. Moreover, the CPSO obtains some solutions better than those previously reported in the literature.