Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Evolutionary Computation
Reference point based multi-objective optimization using evolutionary algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Objective reduction in evolutionary multiobjective optimization: Theory and applications
Evolutionary Computation
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
IEEE Transactions on Evolutionary Computation
PISA: a platform and programming language independent interface for search algorithms
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Controlling dominance area of solutions and its impact on the performance of MOEAs
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Stochastic algorithms assessment using performance profiles
Proceedings of the 13th annual conference on Genetic and evolutionary computation
jMetal: A Java framework for multi-objective optimization
Advances in Engineering Software
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Many-Objective optimization: an engineering design perspective
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
A scalable multi-objective test problem toolkit
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
The balance between proximity and diversity in multiobjective evolutionary algorithms
IEEE Transactions on Evolutionary Computation
A new multi-objective evolutionary algorithm based on a performance assessment indicator
Proceedings of the 14th annual conference on Genetic and evolutionary computation
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In this paper, we propose an evolutionary algorithm for handling many-objective optimization problems called MyO-DEMR (many-objective differential evolution with mutation restriction). The algorithm uses the concept of Pareto dominance coupled with the inverted generational distance metric to select the population of the next generation from the combined multi-set of parents and offspring. Furthermore, we suggest a strategy for the restriction of the difference vector in DE operator in order to improve the convergence property in multi-modal fitness landscape. We compare MyO-DEMR with other state-of-the-art multiobjective evolutionary algorithms on a number of multiobjective optimization problems having up to 20 dimensions. The results reveal that the proposed selection scheme is able to effectively guide the search in high-dimensional objective space. Moreover, MyO-DEMR demonstrates significantly superior performance on multi-modal problems comparing with other DE-based approaches.