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GECCO
2007
Springer
300views Optimization» more  GECCO 2007»
15 years 6 months ago
Methodology to select solutions from the pareto-optimal set: a comparative study
The resolution of a Multi-Objective Optimization Problem (MOOP) does not end when the Pareto-optimal set is found. In real problems, a single solution must be selected. Ideally, t...
José C. Ferreira, Carlos M. Fonseca, Ant&oa...
CEC
2009
IEEE
15 years 4 months ago
Performance of infeasibility driven evolutionary algorithm (IDEA) on constrained dynamic single objective optimization problems
Abstract—A number of population based optimization algorithms have been proposed in recent years to solve unconstrained and constrained single and multi-objective optimization pr...
Hemant K. Singh, Amitay Isaacs, Trung Thanh Nguyen...
IPPS
2007
IEEE
15 years 6 months ago
Distributed Adaptive Particle Swarm Optimizer in Dynamic Environment
Particle Swarm Optimization (PSO) is a population-based stochastic optimization technique, which can be used to find an optimal, or near optimal, solution to a numerical and quali...
Xiaohui Cui, Thomas E. Potok
CORR
2008
Springer
129views Education» more  CORR 2008»
14 years 12 months ago
Evolving Dynamic Change and Exchange of Genotype Encoding in Genetic Algorithms for Difficult Optimization Problems
The application of genetic algorithms (GAs) to many optimization problems in organizations often results in good performance and high quality solutions. For successful and efficien...
Maroun Bercachi, Philippe Collard, Manuel Clergue,...
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
15 years 6 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart