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Self-calibrating Strategies for Evolutionary Approaches that Solve Constrained Combinatorial Problems

Elizabeth MonteroContact Information and María-Cristina RiffContact Information

(1)  Departamento de Informática, Universidad Técnica Federico Santa María, Valparaíso, Chile
Abstract
In this paper, we evaluate parameter control strategies for evolutionary approaches to solve constrained combinatorial problems. For testing, we have used two well known evolutionary algorithms that solve the Constraint Satisfaction Problems GSA and SAW. We contrast our results with REVAC, a recently proposed technique for parameter tuning.

Keywords  Parameter Control - Evolutionary Algorithms

The authors were supported by the Fondecyt Project 1080110.

Contact Information Elizabeth Montero
Email: Elizabeth.Montero@inf.utfsm.cl

Contact Information María-Cristina Riff
Email: Maria-Cristina.Riff@inf.utfsm.cl
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