Foundations of evolutionary multi-objective optimization

• Evolutionary algorithms are in particular successful for multiobjective optimization problems • Why? • Multi-objective problems deal with several (conflicting) objective functions. • Compute different trade offs with respect to the given objective functions (Pareto front, Pareto optimal set). • Population of an EA may be used to compute/approximate the Pareto front. This tutorial: Theore'cal understanding of EAs for mul'-­‐objec've op'miza'on Analyze basic features of such algorithms and point out differences