Minimum-weight two-connected spanning networks
Mathematical Programming: Series A and B
On the structure of minimum-weight k-connected spanning networks
SIAM Journal on Discrete Mathematics
Network reliability and algebraic structures
Network reliability and algebraic structures
A reliability model applied to emergency service vehicle location
Operations Research
Optimal location of facilities on a network with an unreliable node or link
Information Processing Letters
The Combinatorics of Network Reliability
The Combinatorics of Network Reliability
Integrated Stochastic Supply-Chain Design Models
Computing in Science and Engineering
A bilevel mixed-integer program for critical infrastructure protection planning
Computers and Operations Research
Network location of a reliable center using the most reliable route policy
Computers and Operations Research
Modeling supplier selection and the use of option contracts for global supply chain design
Computers and Operations Research
The Stochastic Multiperiod Location Transportation Problem
Transportation Science
The Effect of Supply Disruptions on Supply Chain Design Decisions
Transportation Science
Reliable Facility Location Design Under the Risk of Disruptions
Operations Research
On n-facility median problem with facilities subject to failure facing uniform demand
Discrete Applied Mathematics
The Reliable Facility Location Problem: Formulations, Heuristics, and Approximation Algorithms
INFORMS Journal on Computing
INOC'11 Proceedings of the 5th international conference on Network optimization
A bilevel fixed charge location model for facilities under imminent attack
Computers and Operations Research
Backup 2-center on interval graphs
Theoretical Computer Science
Optimizing supplier selection with disruptions by chance-constrained programming
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
Reliable facility location design under disruptions
Computers and Operations Research
Process Location and Product Distribution with Uncertain Yields
Operations Research
Simulation optimization embedded particle swarm optimization for reliable server assignment
Proceedings of the Winter Simulation Conference
Facility Location Decisions with Random Disruptions and Imperfect Estimation
Manufacturing & Service Operations Management
Super facilities versus chaining in mitigating disruptions impacts
Computers and Industrial Engineering
Computers and Industrial Engineering
Approximation Algorithms for Integrated Distribution Network Design Problems
INFORMS Journal on Computing
An Efficient Approach for Solving Reliable Facility Location Models
INFORMS Journal on Computing
Protection issues for supply systems involving random attacks
Computers and Operations Research
Unreliable point facility location problems on networks
Discrete Applied Mathematics
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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.