Comparative analysis of models and performance indicators for optimal service facility location

Edoardo Fadda, Daniele Manerba, Gianpiero Cabodi, Paolo Enrico Camurati and Roberto Tadei

Transportation Research Part E: Logistics and Transportation Review, 2021, vol. 145, issue C

Abstract: This study investigates the optimal process for locating generic service facilities by applying and comparing several well-known basic models from the literature. At a strategic level, we emphasize that selecting the right location model to use could result in a problematic and possibly misleading task if not supported by appropriate quantitative analysis. For this reason, we propose a general methodological framework to analyze and compare the solutions provided by several models to obtain a comprehensive evaluation of the location decisions from several different perspectives. Therefore, a battery of key performance indicators (KPIs) has been developed and calculated for the different models’ solutions. Additional insights into the decision process have been obtained through a comparative analysis. The indicators involve topological, coverage, equity, robustness, dispersion, and accessibility aspects. Moreover, a specific part of the analysis is devoted to progressive location interventions over time and identifying core location decisions. Results on randomly generated instances, which simulate areas characterized by realistic geographical or demographic features, are reported to analyze the models’ behavior in different settings and demonstrate the methodology’s general applicability. Our experimental campaign shows that the p-median model behaves very well against the proposed KPIs. In contrast, the maximal covering problem and some proposed back-up coverage models return very robust solutions when the location plan is implemented through several progressive interventions over time.

Keywords: Facility location; Key performance indicators; Back-up coverage; Progressive interventions (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.tre.2020.102174

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