Self-Organizing Maps
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Self-organizing Maps for Pareto Optimization of Airfoils
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
A Variant of Evolution Strategies for Vector Optimization
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
A self-adaptive multiagent evolutionary algorithm for electrical machine design
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Optimal fuzzy logic control for MDOF structural systems using evolutionary algorithms
Engineering Applications of Artificial Intelligence
A multi-objective evolutionary algorithm for examination timetabling
Journal of Scheduling
Journal of Computer and Systems Sciences International
Graph partitioning by multi-objective real-valued metaheuristics: A comparative study
Applied Soft Computing
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
Exploiting comparative studies using criteria: generating knowledge from an analyst's perspective
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Self-adaptation techniques applied to multi-objective evolutionary algorithms
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
A Modified micro Genetic Algorithm for undertaking Multi-Objective Optimization Problems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications
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In this paper, we deal with an important issue generally omitted in the current literature on evolutionary multi-objective optimization: on-line adaptation. We propose a revised version of our micro-GA for multi-objective optimization which does not require any parameter fine-tuning. Furthermore, we introduce in this paper a dynamic selection scheme through which our algorithm decides which is the "best" crossover operator to be used at any given time. Such a scheme has helped to improve the performance of the new version of the algorithm which is called the micro-GA2 (µGA2). The new approach is validated using several test function and metrics taken from the specialized literature and it is compared to the NSGA-II and PAES.