Location of Public Facilities Under Congestion

Robert Aboolian () and Majid Karimi ()
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Robert Aboolian: California State University San Marcos, San Marcos
Majid Karimi: California State University San Marcos, San Marcos

A chapter in Uncertainty in Facility Location Problems, 2023, pp 251-280 from Springer

Abstract: Abstract In this chapter, we present location models for congested public facilities. In contrast with classical location models in which the demand and services are deterministic, we consider settings where consumers generate streams of stochastic demand for service, and service times are stochastic, which leads to congestion in facilities. Because of the congestion, consumers will either wait to receive services or leave the facility without being served. Location-allocation decisions in congested facilities are particularly important in applications of public service systems, with applications ranging from the design of preventive healthcare networks to welfare service systems. We particularly focus on congestion models in public location theory. After a brief review of congestion models and their impact on our understanding of public facilities, we detail state-of-the-art research in the operations research literature. To organize our view of the current literature, we present a unifying classification of public facility location models with congestion and present relevant models, solution approaches, and their strengths and limitations. We conclude this chapter by discussing the current research opportunities for location scientists in public location theory from the lens of stochastic modeling and congestion.

Keywords: Location of public facilities; Congested facilities; Service system design (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-3-031-32338-6_10

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