Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Constraint Method-Based Evolutionary Algorithm (CMEA) for Multiobjective Optimization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
The evolution of optimality: de novo programming
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Interactive Multiobjective Evolutionary Algorithms
Multiobjective Optimization
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Multi-objective optimization, also known as multi-criteria decision making in the field of operations research, is a common task in many financial engineering problems. Several alternative approaches to multi-objective optimization have been proposed in operations research. Depending on when the so-called decision maker introduces his preferences, three approaches to multi-criteria decision making can be distinguished: a priori decision making, interactive decision making, and finally a posteriori decision making. This paper suggests a new interactive multi-criteria decision making scheme which combines these three approaches in a single multi-objective optimization framework. In contrast to most operations research approaches, the new scheme is based on evolutionary algorithms due to of their flexibility regarding the type of objectives and constraints. This way the new scheme allows de novo programming, which enables the decision maker to refine the problem definition and to reduce the size of the objective space iteratively.