Efficiency of Metaheuristic Principles in Pareto Front Approximation

This research paper focuses on a case study of metaheuristic principles developed to obtain good Pareto front approximation, which is usually searched for whenever the mathematical model needs to optimize two or more contradictory objectives at the same time. The necessity of Pareto front approximation comes from the assumption that the full set of non-dominated location problem solutions is hard to complete in reasonable computational time. Therefore, the attention is paid to various heuristic approaches, which can approximate the original Pareto front in different levels. The main goal of this paper is to compare the metaheuristics created so far in terms of the quality of the results achieved. All suggested algorithms will be experimentally verified, and their efficiency will be studied making use of a real-world dataset.