Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
The Pareto Envelope-Based Selection Algorithm for Multi-objective Optimisation
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing)
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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The concept of optimization refers to the process of finding one or more feasible solutions of a problem which corresponds to the extreme values (either maximum or minimum) of one or more objective functions. Initial approaches to optimization were focused on the case of solving problems involving only one objective. However, as most real-world optimization problems involve many objectives the research on this area has rapidly broaden this attention to encompass what has been called multi-objective optimization.