Ra-dominance: A new dominance relationship for preference-based evolutionary multiobjective optimization

Evolutionary Multiobjective Optimization Using a Fuzzy-based Dominance Concept

One aspect that is often disregarded in evolutionary multiobjective research is the fact that the solution of a problem involves not only search but decision making. Most of approaches concentrate on adapting an evolutionary algorithm to generate the Pareto frontier. In this work we present a new idea to incorporate preferences in MOEA. We introduce a binary fuzzy preference relation that expre...

A Non-parametric Statistical Dominance Operator for Noisy Multiobjective Optimization

This paper describes and evaluates a new noise-aware dominance operator for evolutionary algorithms to solve the multiobjective optimization problems (MOPs) that contain noise in their objective functions. This operator is designed with the Mann-Whitney U -test, which is a non-parametric (i.e., distribution-free) statistical significance test. It takes objective value samples of given two indiv...

Dominance-Based Rough Set Approach to Interactive Multiobjective Optimization

In this chapter, we present a new method for interactive multiobjective optimization, which is based on application of a logical preference model built using the Dominance-based Rough Set Approach (DRSA). The method is composed of two main stages that alternate in an interactive procedure. In the first stage, a sample of solutions from the Pareto optimal set (or from its approximation) is gener...

A New Evolutionary Approach for Multiobjective Optimization

Efficient and Reliable Evolutionary Multiobjective Optimization Using ε-Dominance Archiving and Adaptive Population Sizing