A hypergraph multi-exchange heuristic for the single-source capacitated facility location problem

Tran, Trung Hieu; Scaparra, Maria Paola; O’Hanley, J.R.

doi:10.1016/j.ejor.2017.04.032

Cited by 13 publications

(2 citation statements)

References 46 publications

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“…Management Sciences [25], Algorithm Design [9], Geographical Information Systems [18] and many more. Also, this problem has been studied in different settings such as Uncapasitated [14], Capasited [29], Multistage [7], Hierarchical [12], Stochastic Demand [17], Unreliable Links [21], Under Disruptions [1] and their different combinations [22]. The problem has got applications in different domains of society including health care [2], defense [15], etc.…”

Section: Related Workmentioning

confidence: 99%

A Social Distancing-Based Facility Location Approach for Combating COVID-19

Banerjee¹,

Pal²,

Singhamahapatra³

2021

Preprint

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In this paper, we introduce and study the problem of facility location along with the notion of 'social distancing'. The input to the problem is the road network of a city where the nodes are the residential zones, edges are the road segments connecting the zones along with their respective distance. We also have the information about the population at each zone, different types of facilities to be opened and in which number, and their respective demands in each zone. The goal of the problem is to locate the facilities such that the people can be served and at the same time the total social distancing is maximized. We formally call this problem as the Social Distancing-Based Facility Location Problem. We mathematically quantify social distancing for a given allocation of facilities and proposed an optimization model. As the problem is NP-Hard, we propose a simulation-based and heuristic approach for solving this problem. A detailed analysis of both methods has been done. We perform an extensive set of experiments with synthetic datasets. From the results, we observe that the proposed heuristic approach leads to a better allocation compared to the simulation-based approach.

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Section: Related Workmentioning

confidence: 99%

A Social Distancing-Based Facility Location Approach for Combating COVID-19

Banerjee¹,

Pal²,

Singhamahapatra³

2021

Preprint

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“…Certain variations of the facility location problem were proved to be NP-Hard in the works of [2,3]. Among the solution methods for facility location problems are mathematical models [4] and heuristics [5]. In the following paragraphs, we provide an overview of the most common types of the facility location problem, namely, capacitated and uncapacitated problems, single-and multi-facility problems, covering problems, center problems, median problems, and location-allocation problems.…”

Section: Introductionmentioning

confidence: 99%

A Risk-Based Location-Allocation Approach for Weapon Logistics

Çetinkaya

Haffar

2018

Logistics

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Abstract:Governments have vital missions, such as securing their nation from many internal or external risks/threats. Thus, they prepare themselves against different scenarios. The most common scenario for all countries is "facing attacks from other countries". However, training for these scenarios is not possible because military exercises are too expensive. The contribution of this paper is a scientific approach proposed for such a scenario. A mathematical model is developed to allocate different weapon types to a set of candidate locations (demand nodes, the military installations that need weapons) while minimizing total transportation costs, setup costs, and allocation risk. The risk arises from allocating the weapons to other military units as backups during a conflict. The risk increases when one military unit allocates their weapons to another unit during attacks. The mathematical model is tested on a case study problem of Turkish Land Forces. This case study is solved in 14 min, and the optimal total transportation and setup costs are determined. Since it is very important to make quick decisions during an attack, this scientific approach and computational time can be useful for military decision makers. Additionally, the results of this study can guarantee that any attack can be handled with the minimum cost and risk.

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