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Probabilistic, Maximal Covering Location—Allocation Models forCongested Systems
Author(s) -
Marianov Vladimir,
Serra Daniel
Publication year - 1998
Publication title -
journal of regional science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.171
H-Index - 79
eISSN - 1467-9787
pISSN - 0022-4146
DOI - 10.1111/0022-4146.00100
Subject(s) - probabilistic logic , computer science , service (business) , computer network , queue , heuristic , server , queueing theory , ticket , population , node (physics) , operations research , mathematical optimization , mathematics , economics , engineering , artificial intelligence , demography , structural engineering , sociology , economy
When dealing with the design of service networks, such as health andemergency medical services, banking or distributed ticket‐selling services, the location of servicecenters has a strong influence on the congestion at each of them, and, consequently, on thequality of service. In this paper, several probabilistic maximal coveringlocation—allocation models with constrained waiting time for queue length are presentedto consider service congestion. The first model considers the location of a given number ofsingle‐server centers such that the maximum population is served within a standard distance, andnobody stands in line for longer than a given time or with more than a predetermined number ofother users. Several maximal coverage models are then formulated with one or more servers perservice center. A new heuristic is developed to solve the models and tested in a 30‐node network.