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Reliability Models for Facility Location: The Expected Failure Cost Case

Reliability Models for Facility Location: The Expected Failure Cost Case Classical facility location models like the P-median problem (PMP) and the uncapacitated fixed-charge location problem (UFLP) implicitly assume that, once constructed, the facilities chosen will always operate as planned. In reality, however, facilities “fail” from time to time due to poor weather, labor actions, changes of ownership, or other factors. Such failures may lead to excessive transportation costs as customers must be served from facilities much farther than their regularly assigned facilities. In this paper, we present models for choosing facility locations to minimize cost, while also taking into account the expected transportation cost after failures of facilities. The goal is to choose facility locations that are both inexpensive under traditional objective functions and also reliable. This reliability approach is new in the facility location literature. We formulate reliability models based on both the PMP and the UFLP and present an optimal Lagrangian relaxation algorithm to solve them. We discuss how to use these models to generate a trade-off curve between the day-to-day operating cost and the expected cost, taking failures into account, and we use these trade-off curves to demonstrate empirically that substantial improvements in reliability are often possible with minimal increases in operating cost. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Transportation Science INFORMS

Reliability Models for Facility Location: The Expected Failure Cost Case

Snyder, Lawrence V.; Daskin, Mark S.
Transportation Science , Volume 39 (3): 17 – Aug 1, 2005
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Publisher
INFORMS
Copyright
Copyright © INFORMS
Subject
Research Article
ISSN
0041-1655
eISSN
1526-5447
DOI
10.1287/trsc.1040.0107
Publisher site
See Article on Publisher Site

Abstract

Classical facility location models like the P-median problem (PMP) and the uncapacitated fixed-charge location problem (UFLP) implicitly assume that, once constructed, the facilities chosen will always operate as planned. In reality, however, facilities “fail” from time to time due to poor weather, labor actions, changes of ownership, or other factors. Such failures may lead to excessive transportation costs as customers must be served from facilities much farther than their regularly assigned facilities. In this paper, we present models for choosing facility locations to minimize cost, while also taking into account the expected transportation cost after failures of facilities. The goal is to choose facility locations that are both inexpensive under traditional objective functions and also reliable. This reliability approach is new in the facility location literature. We formulate reliability models based on both the PMP and the UFLP and present an optimal Lagrangian relaxation algorithm to solve them. We discuss how to use these models to generate a trade-off curve between the day-to-day operating cost and the expected cost, taking failures into account, and we use these trade-off curves to demonstrate empirically that substantial improvements in reliability are often possible with minimal increases in operating cost.

Journal

Transportation Science – INFORMS

Published: Aug 1, 2005

Keywords: Keywords : facility location ; disruptions ; Lagrangian relaxation ; multiobjective optimization

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