Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Pattern Search Algorithms for Bound Constrained Minimization
SIAM Journal on Optimization
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization
Evolutionary Computation
Covariance Matrix Adaptation Revisited --- The CMSA Evolution Strategy ---
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
Experimental comparison of methods to handle boundary constraints in differential evolution
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Evolving Problems to Learn About Particle Swarm Optimizers and Other Search Algorithms
IEEE Transactions on Evolutionary Computation
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Box constraints are possibly the simplest kind of constraints one could think of in real-valued optimization, because it is trivial to detect and repair any violation of them. But so far, the topic has only received marginal attention in the literature compared to the more general formulations, although it is a frequent use case. It is experimentally shown here that different repair methods can have a huge impact on the optimizer's performance when using the covariance matrix self-adaptation evolution strategy (CMSA-ES). Also, two novel repair methods, specially designed for this algorithm, sometimes outperform the traditional ones.