Repeated Refinement Approach to Bi-objective $p$-Location Problems

Abstract

This paper deals with the comparison of different solving techniques for bi-objective $p$-location problems, which can be met very often in many areas of human life including also the health sector and rescue services. Making the final decision on service center locations is usually a complex challenge mainly due to several years' impact on the efficiency of the service provided. Moreover, any good or bad decision directly affects the accessibility of urgent care in case of emergency. From this point of view, the optimal service center deployment can be formulated as a bi- or multi-criteria decision-making problem. While obtaining the result of the problem with one objective function follows from solving a simple model, usage of more parallel quality criteria implies the construction of the Pareto front or at least of its approximation. In this paper, we deal with five different heuristic algorithms for processing the solutions of the current set of non-dominated solutions in order to choose the most suitable approach for practice. Suggested theoretical ideas will be studied on the dataset from real Emergency Medical Service System in Slovakia.