Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Evolutionary algorithms for constrained engineering problems
Computers and Industrial Engineering
SAW-ing EAs: adapting the fitness function for solving constrained problems
New ideas in optimization
Using Genetic Algorithms in Engineering Design Optimization with Non-Linear Constraints
Proceedings of the 5th International Conference on Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
A Segregated Genetic Algorithm for Constrained Structural Optimization
Proceedings of the 6th International Conference on Genetic Algorithms
A Decoder-Based Evolutionary Algorithm for Constrained Parameter Optimization Problems
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Evolutionary Computation at the Edge of Feasibility
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
An Adaptive Penalty Scheme In Genetic Algorithms For Constrained Optimiazation Problems
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
How to Solve It: Modern Heuristics
How to Solve It: Modern Heuristics
Self-Adaptive Genetic Algorithms with Simulated Binary Crossover
Evolutionary Computation
Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization
Evolutionary Computation
Evolutionary algorithms for constrained parameter optimization problems
Evolutionary Computation
Evolutionary programming techniques for constrained optimizationproblems
IEEE Transactions on Evolutionary Computation
Stochastic ranking for constrained evolutionary optimization
IEEE Transactions on Evolutionary Computation
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A parameter-less adaptive penalty scheme for steady-state genetic algorithms applied to constrained optimization problems is proposed. For each constraint, a penalty parameter is adaptively computed along the run according to information extracted from the current population such as the existence of feasible individuals and the level of violation of each constraint. Using real coding, rank-based selection, and operators available in the literature, very good results are obtained.