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Reliability Models for Facility Location: The Expected Failure Cost Case
 Transportation Science
, 2004
"... Classical facility location models like the Pmedian problem (PMP) and the uncapacitated fixedcharge 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 ..."
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Cited by 52 (12 self)
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Classical facility location models like the Pmedian problem (PMP) and the uncapacitated fixedcharge 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 tradeo# curve between the daytoday operating cost and the expected cost taking failures into account, and use these tradeo# curves to demonstrate empirically that substantial improvements in reliability are often possible with minimal increases in operating cost.
The Stochastic Location Model with Risk Pooling
 EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
, 2007
"... In this paper, we present a stochastic version of the Location Model with Risk Pooling (LMRP) that optimizes location, inventory, and allocation decisions under random parameters described by discrete scenarios. The goal of our model (called the stochastic LMRP, or SLMRP) is to find solutions that m ..."
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Cited by 28 (4 self)
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In this paper, we present a stochastic version of the Location Model with Risk Pooling (LMRP) that optimizes location, inventory, and allocation decisions under random parameters described by discrete scenarios. The goal of our model (called the stochastic LMRP, or SLMRP) is to find solutions that minimize the expected total cost (including location, transportation, and inventory costs) of the system across all scenarios. The location model explicitly handles the economies of scale and riskpooling effects that result from consolidating inventory sites. The SLMRP framework can also be used to solve multicommodity and multiperiod problems. We present a Lagrangianrelaxation–based exact algorithm for the SLMRP. The Lagrangian subproblem is a nonlinear integer program, but it can be solved by a loworder polynomial algorithm. We discuss simple variablefixing routines that can drastically reduce the size of the problem. We present quantitative and qualitative computational results on problems with up to 150 nodes and 9 scenarios, describing both algorithm performance and solution behavior as key parameters change.
Stochastic pRobust Location Problems
, 2004
"... Many objectives have been proposed for optimization under uncertainty. The typical stochastic programming objective of minimizing expected cost may yield solutions that are inexpensive in the long run but perform poorly under certain realizations of the random data. On the other hand, the typical ro ..."
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Cited by 22 (4 self)
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Many objectives have been proposed for optimization under uncertainty. The typical stochastic programming objective of minimizing expected cost may yield solutions that are inexpensive in the long run but perform poorly under certain realizations of the random data. On the other hand, the typical robust optimization objective of minimizing maximum cost or regret tends to be overly conservative, planning against a disastrous but unlikely scenario. In this paper, we present facility location models that combine the two objectives by minimizing the expected cost while bounding the relative regret in each scenario. In particular, the models seek the minimumexpectedcost solution that is probust; i.e., whose relative regret is no more than 100p% in each scenario.
Facility Location in SUpply Chain Design
, 2003
"... In this chapter we outline the importance of facility location decisions in supply chain design. We begin with a review of classical models including the traditional fixed charge facility location problem. We then summarize more recent research aimed at expanding the context of facility location ..."
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Cited by 13 (3 self)
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In this chapter we outline the importance of facility location decisions in supply chain design. We begin with a review of classical models including the traditional fixed charge facility location problem. We then summarize more recent research aimed at expanding the context of facility location decisions to incorporate additional features of a supply chain including LTL vehicle routing, inventory management, robustness, and reliability.
Integrated Modeling and Simulation of Lunar Exploration Campaign Logistics
, 2007
"... As NASA prepares to establish a manned outpost on the lunar surface, it is essential to consider the logistics of both the construction and operation of this outpost. This thesis presents an interplanetary supply chain management and logistics planning and simulation software tool, SpaceNet, develop ..."
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Cited by 3 (1 self)
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As NASA prepares to establish a manned outpost on the lunar surface, it is essential to consider the logistics of both the construction and operation of this outpost. This thesis presents an interplanetary supply chain management and logistics planning and simulation software tool, SpaceNet, developed to assist mission architects, planners, systems engineers and logisticians in performing analysis on what will be needed to support future human exploration missions, primarily in the EarthMoonMars system. Also presented in this thesis are the results of numerous trade studies performed using SpaceNet to determining the best mix of mission types (prepositioning, carryalong and resupply) to achieve sustainable, robust space exploration. These trade studies focus on analyzing notional mission architectures in terms of scientific benefit, logistical overhead and robustness to campaign level risks such as flight delays, flight cancellations and uncertain demand parameters. The significant findings presented in this thesis broadly fall into three categories: a demonstration of the value of integrated modeling and simulation of campaign logistics,
Reliable multiproduct multivehicle multitype link logistics network design: A hybrid heuristic algorithm
"... Abstract This paper considers the reliable multiproduct multivehicle multitype link logistics network design problem (RMLNDP) with system disruptions, which is concerned with facilities locating, transshipment links constructing, and also allocating them to the customers in order to satisfy thei ..."
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Abstract This paper considers the reliable multiproduct multivehicle multitype link logistics network design problem (RMLNDP) with system disruptions, which is concerned with facilities locating, transshipment links constructing, and also allocating them to the customers in order to satisfy their demand with minimum expected total cost (including locating costs, link constructing costs, and also expected transshipment costs in normal and disruption conditions). The motivating application of this class of problem is in multiproduct, multivehicle, and multitype link logistics network design regarding to system disruptions simultaneously. In fact, the decision makers in this area are not only concerned with the facility locating costs, link constructing costs, and logistical costs of the system but also by focusing on the several system disruption states in order to be able to provide a reliable sustainable multi configuration logistic network system. All facility location plans, link construction plans and also link transshipment plans of demands in the problem must be efficiently determined while considering the several system disruptions. The problem is modeled as a mixed integer programming (MIP) model. Also, a hybrid heuristic, based on linear programming (LP) relaxation approach, is proposed. Computational experiments illustrate that the provided algorithm will be able to substantially outperform the proposed integer programming model in terms of both finding and verifying the efficient optimal (or near optimal) solution at a reasonable processing time.
USING ENGINEERING METHODOLOGIES TO DESIGN A ROBUST AND LESS COMPLEX
"... This study reports on the development of a collaborative information system for a truck and bus manufacturing company, to be used by their prototype assembly plant and production plant, via a unique approach that combines Axiomatic Design, Quality Function ..."
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This study reports on the development of a collaborative information system for a truck and bus manufacturing company, to be used by their prototype assembly plant and production plant, via a unique approach that combines Axiomatic Design, Quality Function
The Expected Failure Cost Case
, 2004
"... Classical facility location models like the Pmedian problem (PMP) and the uncapacitated fixedcharge 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, ..."
Abstract
 Add to MetaCart
Classical facility location models like the Pmedian problem (PMP) and the uncapacitated fixedcharge 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 tradeoff curve between the daytoday operating cost and the expected cost taking failures into account, and use these tradeoff curves to demonstrate empirically that substantial improvements in reliability are often possible with minimal increases in operating cost. 1