Evolutionary Design by Computers with CDrom
Evolutionary Design by Computers with CDrom
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Towards Creative Evolutionary Systems with Interactive Genetic Algorithm
Applied Intelligence
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Multiobjective Satisfaction within an Interactive Evolutionary Design Environment
Evolutionary Computation
Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows
Applied Intelligence
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Journal of Heuristics
Interactive Evolutionary Computation-Based Hearing Aid Fitting
IEEE Transactions on Evolutionary Computation
Protein Folding in Simplified Models With Estimation of Distribution Algorithms
IEEE Transactions on Evolutionary Computation
A Drug Candidate Design Environment Using Evolutionary Computation
IEEE Transactions on Evolutionary Computation
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In this paper we deal with a real-world routing problem that consists of finding the best route for an oceanographic campaign. The planning task involves setting up the initial route and managing the route variations along the way. Bearing in mind the idea of building an experimental tool to support the decision making process of the expert when planning the route, two different approaches to solve the problem were developed. First of all, we assumed that the problem was well characterized by the initial description of the expert, using as fitness function the time employed in the route and applying classical local search optimization heuristics. The difficulty of a precise constraint definition and the infeasibility of mathematically describing all the evaluation criteria of the expert led us towards interactive optimization as a way to introduce the knowledge of the expert. According to the results, this last approach was able to provide satisfactory solutions.