The competitive facility location problem under disruption risks

Zhang, Ying; Snyder, Lawrence; Ralphs, Ted K.; Xue, Zhang

doi:10.1016/j.tre.2016.07.002

Cited by 51 publications

(11 citation statements)

References 42 publications

(63 reference statements)

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“…However, they studied a variant in which two players position several facilities each, and did not extend the model to a greater number of players. Zhang et al considered a discrete competitive location model in which there are finitely many clients and finitely many potential facility locations [14]. Their model, while similar to our model in theme, bears little resemblance to Hotelling's original game.…”

Section: Introductionmentioning

confidence: 83%

Fault-Tolerant Hotelling Games

Avin

Cohen

Lotker

et al. 2018

EAI/Springer Innovations in Communication and Computing

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The n-player Hotelling game calls for each player to choose a point on the line segment, so as to maximize the size of his Voronoi cell. This paper studies fault-tolerant versions of the Hotelling game. Two fault models are studied: line faults and player faults. The first model assumes that the environment is prone to failure: with some probability, a disconnection occurs at a random point on the line, splitting it into two separate segments and modifying each player's Voronoi cell accordingly. A complete characterization of the Nash equilibria of this variant is provided for every n. Additionally, a one to one correspondence is shown between equilibria of this variant and of the Hotelling game with no faults. The second fault model assumes the players are prone to failure: each player is removed from the game with i.i.d. probability, changing the payoffs of the remaining players accordingly. It is shown that for n ≥ 3 this variant of the game has no Nash equilibria.

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Section: Introductionmentioning

confidence: 83%

Fault-Tolerant Hotelling Games

Avin

Cohen

Lotker

et al. 2018

EAI/Springer Innovations in Communication and Computing

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“…Based on the conducted analysis, their results showed the capability of the proposed meta-heuristic algorithm of obtaining high-quality solutions. Zhang et al [11] had considered a competitive facility location problem with disruption and had formulated the problem as a bilevel integer problem. A variable neighborhood decomposition search includes variable fixing and cut generation developed in order to solve the problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Influence of Two Different Producers in a Competitive Location Problem

2019

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Facility location of two producers with preference of customers is discussed in this paper. Because of differences between two producers in terms of their influence on the market, the problem is formulated as a bi-level integer mathematical programming model with binary variables. It is considered that both leader and follower have some facilities at first and are going to open new facilities and this may lead to make changes in allocation of facilities and customers. To solve the problem, two metaheuristics algorithm based on genetic algorithm (GA) and hybrid of genetic algorithm and ant colony optimization (ACO) are proposed. In the first section of each algorithm, the location of facilities for two producers is determined and in the second section, each customer selects a facility. Upper bound of the competitive facility location problem is determined by solving the upper-level problem as an integer linear programming model without considering the follower's decision. To evaluate the efficiency of proposed algorithms, enumeration technique is used to find optimal solution. Computational results show that all of the developed algorithms are capable of achieving optimal solution for small size problems and high-quality solution in reasonable computational time for medium and large-scale problems.

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“…Chen et al [28] presented a location-inventory problem regarding disruptions and assumed that facilities may fail independently with an equal probability. Last but not the least, Zhang et al [34] devised a discrete competitive [17] 2002 * * * [41] 2003 * * [42] 2005 * * * * [43] 2007 * * * [2] 2008 * * * * [18] 2010 * * * * [28] 2011 * * * * [44] 2012 * * * * [21] 2014 * * * [3] 2015 * * * [45] 2015 * * * * * [23] 2016 * * * * * Our work -* * * * * * * * facility location problem under facility failure patterns and developed a variable neighborhood decomposition search heuristic to solve their problem.…”

Section: Facility Disruptionmentioning

confidence: 99%

A hybrid Markov process-mathematical programming approach for joint location-inventory problem under supply disruptions

2018

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This paper introduces a joint location-inventory problem, in which facilities become temporarily unavailable. A hybrid approach based on the Markov process and mathematical programming techniques is presented to design the distribution network of a supply chain in an integrated manner. In the first phase, the Markov process derives some performance features of inventory policy. In the second phase, using outputs of the Markov process, the location-inventory problem is formulated as a mixed-integer nonlinear programming model. Moreover, a robust possibilistic programming approach is utilized, which is able to provide a more stable supply chain structure under almost all possible values of imprecise parameters. Since the proposed problem is complicated to solve by means of exact methods, we develop a simulated annealing algorithm in order to find near-optimal solutions in reasonable computational times. The obtained computational results reveal the efficiency and effectiveness of the proposed solution approach. Finally, some insights are provided and the performance of the proposed robust optimization approach is compared to traditional possibilistic chance constrained method.

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The competitive facility location problem under disruption risks

Cited by 51 publications

References 42 publications

Fault-Tolerant Hotelling Games

Fault-Tolerant Hotelling Games

Influence of Two Different Producers in a Competitive Location Problem

A hybrid Markov process-mathematical programming approach for joint location-inventory problem under supply disruptions

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