An Efficient Adjustment of Genetic Algorithm for Pareto Front Determination

The Pareto front determination is an important part of multiobjective problem solving when two or more contradictory objectives must be considered. This paper deals with the emergency service system design problem where the demand for minimal average response time stands in opposition to the demand that maximal travel time over all users should be as small as possible. On the contrary to the iterative approach employing mathematical programming, we focus on adjustment of genetic algorithm which builds the Pareto front by updating an elite set of individuals. As the genetic algorithm belongs to the family of metaheuristics, it is commonly awaited that its performance is very sensitive to setting of its parameters. That is why the focus of this paper is devoted to such method of parameter setting, which is most suitable for efficient estimate Pareto front determination by the genetic algorithm. (C) 2019 The Authors. Published by Elsevier B.V.