Abstract
A developed version of Generalized Differential Evolution, GDE3, is proposed. GDE3 is an extension of Differential Evolution (DE) for global optimization with an arbitrary number of objectives and constraints. In the case of a problem with a single objective and without constraints GDE3 falls back to the original DE. GDE3 improves earlier GDE versions in the case of multi-objective problems by giving a better distributed solution. Performance of GDE3 is demonstrated with a set of test problems and the results are compared with other methods.
1 Introduction
During the last 15 years, Evolutionary Algorithms (EAs) have gained popularity in solving difficult multiobjective optimization problems (MOOPs) since EAs are capable of dealing with objective functions, which are not mathematically well behaving, e.g., discontinuous, non-convex, multi-modal, and non-differentiable. Multi-objective EAs (MOEAs) are also capable of providing multiple solution candidates in a single run, which is desirable with MOOPs.
6 Conclusions and Future Research
The third evolution version of Generalized Differential Evolution, GDE3, is proposed. GDE3 is designed for any number of objectives and constraints without introducing any extra control parameters to the original DE. In the case of unconstrained single-objective optimization problems, GDE3 is exactly the same as the original DE.
