Performance Assessment of Generalized Differential Evolution 3 (GDE3) with a Given Set of Problems


This paper presents results for the CEC 2007 Special Session on Performance Assessment of Multi- Objective Optimization Algorithms where Generalized Differential Evolution 3 (GDE3) has been used to solve a given set of test problems. The set consist of 19 problems having two, three, or five objectives. Problems have different properties in the sense of separability, modality, and geometry of the Pareto-front According to the results, a near optimal set of solutions was found in the majority of the problems. Rotated problems given caused more difficulty than the other problems. Performance metrics indicate that obtained approximation sets were even better than provided reference sets for many problems.