The probabilistic p -center problem: Planning service for potential customers

Martínez-Merino, Luisa I.; Albareda-Sambola, Maria; Rodríguez‐Chía, Antonio M.

doi:10.1016/j.ejor.2017.03.043

Cited by 14 publications

(2 citation statements)

References 24 publications

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“…Recall from Martínez-Merino et al (2017) that the Probabilistic pCP (PpCP) is defined as the variant of the pCP where sites represent potential demand points, and the locations of the p centers have to be decided before the actual subset of sites that need to be served is revealed. In this problem, the goal is to minimize the expected maximum distance between a site with demand and its closest center.…”

Section: Saa For the Probabilistic P-center Problemmentioning

confidence: 99%

The stratified p-center problem

Albareda-Sambola

Martínez-Merino

Rodríguez‐Chía

2019

Computers & Operations Research

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This work presents an extension of the p-center problem. In this new model, calledStratified p-Center Problem (SpCP), the demand is concentrated in a set of sites and the population of these sites is divided into different strata depending on the kind of service that they require. The aim is to locate p centers to cover the different types of services demanded minimizing the weighted average of the largest distances associated with each of the different strata. In addition, it is considered that more than one stratum can be present at each site. Different formulations, valid inequalities and preprocessings are developed and compared for this problem. An application of this model is presented in order to implement a heuristic approach based on the Sample Average Approximation method (SAA) for solving the probabilistic p-center problem in an efficient way.

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Section: Saa For the Probabilistic P-center Problemmentioning

confidence: 99%

The stratified p-center problem

Albareda-Sambola

Martínez-Merino

Rodríguez‐Chía

2019

Computers & Operations Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…Among other similar facility location problems are Probabilistic p-Center (Martínez-Merino et al, 2017), α-All-Neighbour p-Center (Khuller et al, 2000), Capacitated p-Center (Kramer et al, 2020), and p-Median (Mladenović et al, 2007) problems.…”

Section: Introductionmentioning

confidence: 99%