Study of Combination of Evolutionary Multi-objective Optimization with Interactive Evolutionary Computation Using Pseudo-user

― Evaluation experiments with architecture floor plan as task ―

Abstract

We investigate the combinatorial effect of evolutionary multi-objective optimization (EMO) with interactive evolutionary computation (IEC). The purposes and combination ways of several presented EMO+IEC researches are different. We evaluated seven combination ways of four EMO objectives given by fitness functions and one IEC objective given by a pseudo-IEC user outputting stable evaluation regardless repeated experiments in our previous experiments. In this paper, we extend experimental conditions to 39 and evaluate them: 3 pseudo-users * 13 combination ways of 4+1 objectives. We also consider features of this system.