Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Journal of Global Optimization
Combining convergence and diversity in evolutionary multiobjective optimization
Evolutionary Computation
A Variant of Evolution Strategies for Vector Optimization
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
Towards a quick computation of well-spread pareto-optimal solutions
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Improving PSO-Based multi-objective optimization using crowding, mutation and ∈-dominance
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Accelerating convergence using rough sets theory for multi-objective optimization problems
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
An improved secondary ranking for many objective optimization problems
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Improving the efficiency of -dominance based grids
Information Sciences: an International Journal
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Multiobjective evolutionary algorithms for multivariable PI controller design
Expert Systems with Applications: An International Journal
Asymmetric pareto-adaptive scheme for multiobjective optimization
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Comparison of design concepts in multi-criteria decision-making using level diagrams
Information Sciences: an International Journal
Elitist archiving for multi-objective evolutionary algorithms: to adapt or not to adapt
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
HEMH2: an improved hybrid evolutionary metaheuristics for 0/1 multiobjective knapsack problems
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
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Efficiency has become one of the main concerns in evolutionary multiobjective optimization during recent years. One of the possible alternatives to achieve a faster convergence is to use a relaxed form of Pareto dominance that allows us to regulate the granularity of the approximation of the Pareto front that we wish to achieve. One such relaxed forms of Pareto dominance that has become popular in the last few years is ε-dominance, which has been mainly used as an archiving strategy in some multiobjective evolutionary algorithms. Despite its advantages, ε-dominance has some limitations. In this paper, we propose a mechanism that can be seen as a variant of ε-dominance, which we call Pareto-adaptive ε-dominance (paε-dominance). Our proposed approach tries to overcome the main limitation of ε-dominance: the loss of several nondominated solutions from the hypergrid adopted in the archive because of the way in which solutions are selected within each box.