Proceedings of: Fifth International Conference on Future Computational Technologies and Applications (FUTURE COMPUTING 2013), Valencia, Spain, May 27 - June 1, 2013Archiving procedures are a key parameter for Multi-objective evolutionary algorithms, since they guarantee the algorithm convergence and the good spread of the obtained solutions in the final Pareto front. For many practical applications, the cost of the algorithm is clearly dominated by the computational cost of the underlying fitness functions, allowing complex processes to be incorporated into the archiving procedure. This work presents a study of the archiving technique for evolutionary polygonal approximation (the division of a given curve into a set of n segments represente...
Existing multiobjective evolutionary algorithms (MOEAs) tackle a multiobjective problem either as a ...
During the last decades, numerous heuristic search methods for solving multi-objective optimization ...
The issue of obtaining a well-converged and well-distributed set of Pareto optimal solutions efficie...
Proceedings of: Fifth International Conference on Future Computational Technologies and Applications...
Proceedings of: 10th International Symposium on Distributed Computing and Artificial Intelligence . ...
It is crucial to obtain automatically and efficiently a well-distributed set of Pareto optimal solut...
In this paper, a polygonal approximation approach based on a multi-objective genetic algorithm is pr...
htmlabstractObjective-space discretization is a popular method to control the elitist archive size f...
Copyright © 2003 IEEE. Personal use of this material is permitted. Permission from IEEE must be obta...
Approximation-Guided Evolution (AGE) [4] is a recently presented multi-objective algorithm that outp...
International audienceIn this paper, a polygonal approximation approach based on a multi-objective g...
Special Issue: Multi-objective metaheuristics for multi-disciplinary engineering applicationsThis wo...
Abstract—Archives have been widely used in evolutionary multi-objective optimization in order to sto...
Abstract- The trade-off between obtaining a well-converged and well-distributed set of Pareto optima...
Abstract- The issue of obtaining a well-converged and well-distributed set of Pareto optimal solutio...
Existing multiobjective evolutionary algorithms (MOEAs) tackle a multiobjective problem either as a ...
During the last decades, numerous heuristic search methods for solving multi-objective optimization ...
The issue of obtaining a well-converged and well-distributed set of Pareto optimal solutions efficie...
Proceedings of: Fifth International Conference on Future Computational Technologies and Applications...
Proceedings of: 10th International Symposium on Distributed Computing and Artificial Intelligence . ...
It is crucial to obtain automatically and efficiently a well-distributed set of Pareto optimal solut...
In this paper, a polygonal approximation approach based on a multi-objective genetic algorithm is pr...
htmlabstractObjective-space discretization is a popular method to control the elitist archive size f...
Copyright © 2003 IEEE. Personal use of this material is permitted. Permission from IEEE must be obta...
Approximation-Guided Evolution (AGE) [4] is a recently presented multi-objective algorithm that outp...
International audienceIn this paper, a polygonal approximation approach based on a multi-objective g...
Special Issue: Multi-objective metaheuristics for multi-disciplinary engineering applicationsThis wo...
Abstract—Archives have been widely used in evolutionary multi-objective optimization in order to sto...
Abstract- The trade-off between obtaining a well-converged and well-distributed set of Pareto optima...
Abstract- The issue of obtaining a well-converged and well-distributed set of Pareto optimal solutio...
Existing multiobjective evolutionary algorithms (MOEAs) tackle a multiobjective problem either as a ...
During the last decades, numerous heuristic search methods for solving multi-objective optimization ...
The issue of obtaining a well-converged and well-distributed set of Pareto optimal solutions efficie...