A collection of test problems for constrained global optimization algorithms
A collection of test problems for constrained global optimization algorithms
Test Examples for Nonlinear Programming Codes
Test Examples for Nonlinear Programming Codes
Journal of Global Optimization
Using Genetic Algorithms in Engineering Design Optimization with Non-Linear Constraints
Proceedings of the 5th International Conference on Genetic Algorithms
Numerical Comparison of Some Penalty-Based Constraint Handling Techniques in Genetic Algorithms
Journal of Global Optimization
Derivative-Free Filter Simulated Annealing Method for Constrained Continuous Global Optimization
Journal of Global Optimization
Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization
Evolutionary Computation
Evolutionary algorithms for constrained parameter optimization problems
Evolutionary Computation
An adaptive penalty formulation for constrained evolutionary optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Differential evolution in constrained numerical optimization: An empirical study
Information Sciences: an International Journal
Ensemble of constraint handling techniques
IEEE Transactions on Evolutionary Computation
A bi-objective based hybrid evolutionary-classical algorithm for handling equality constraints
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
Search biases in constrained evolutionary optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Evolutionary programming techniques for constrained optimizationproblems
IEEE Transactions on Evolutionary Computation
Stochastic ranking for constrained evolutionary optimization
IEEE Transactions on Evolutionary Computation
Self-adaptive fitness formulation for constrained optimization
IEEE Transactions on Evolutionary Computation
A simple multimembered evolution strategy to solve constrained optimization problems
IEEE Transactions on Evolutionary Computation
An artificial fish swarm algorithm based hyperbolic augmented Lagrangian method
Journal of Computational and Applied Mathematics
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We propose a differential evolution-based algorithm for constrained global optimization. Although differential evolution has been used as the underlying global solver, central to our approach is the penalty function that we introduce. The adaptive nature of the penalty function makes the results of the algorithm mostly insensitive to low values of the penalty parameter. We have also demonstrated both empirically and theoretically that the high value of the penalty parameter is detrimental to convergence, specially for functions with multiple local minimizers. Hence, the penalty function can dispense with the penalty parameter. We have extensively tested our penalty function-based DE algorithm on a set of 24 benchmark test problems. Results obtained are compared with those of some recent algorithms.