Multi-Modal Multi-Objective Evolutionary Optimization for Problems with Solutions of Variable-Length
Amiram Moshaiov, Yosef Breslav, Eliran Farhi · 2021
This paper focuses on solving a special kind of multimodal multi-objective optimization problems (MMOPs) in which solutions are of variable length. First, problem definition and solution framework is suggested to allow using standard multimodal multi-objective evolutionary algorithms (MMEAs) to solve the considered type of problems. Next, a real-life example of the considered type of problems is suggested concerning optimal antennas’ layout-allocation design for a wireless communication network. Finally, a modification to NSGA-II is suggested and employed to solve such layout problems. When compared with other MMEAs, it is shown that the proposed algorithm provides not only better solution diversity in the decision-space, but also solutions with superior performance vectors. It is suggested here that this is attributed to the type of archive that is used here.