A multiobjective fleet location problem solved by adaptation of evolutionary algorithms NSGA-II and SMS-EMOA

The problem of locating naval platforms in the operation region with the aim of maximizing both total radar coverage and critical radar coverage is solved by using multiobjective evolutionary algorithms (moea). non-dominated sorting genetic algorithm-ii (nsga-ii) and s-metric selection evolutionary multiobjective optimization algorithm (sms-emoa) procedures are implemented. experiments show that evolutionary algorithms provide good and diverse alternatives that are considered to be very close to pareto-optimal front. the performances of nsga-ii and sms-emoa approaches are compared employing the hypervolume indicator technique. the performance of nsga-ii is found better in terms of both convergence and diversity.