A comparative survey of service facility location problems

Turkoglu, Derya Celik; Genevois, Müjde Erol

doi:10.1007/s10479-019-03385-x

Cited by 69 publications

(36 citation statements)

References 151 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, there is a small number of approaches that are based on optimally solving the mathematical programming model; See [35], [36], [37], and [38]). Nevertheless, as mentioned, since the under-study problem is an NP-hard one, most of the solution approaches that have been proposed so far follow (meta) heuristic manners; See, for example, [39], [40], and [41].…”

Section: Literature Reviewmentioning

confidence: 99%

Toward unraveling multi-objective optimization problems: A hybrid approach for solving a novel facility location problem

DehghanChenary¹,

Ferdowsi²,

Jolai³

et al. 2022

Preprint

View full text Add to dashboard Cite

<pre>The focus of this paper is to propose a bi-objective mathematical model for a new extension of a multi-period p-mobile hub location problem and then to devise an algorithm for solving it. The developed model considers the impact of the time spent traveling at the hubs' network, the time spent at hubs for processing the flows, and the delay caused by congestion at hubs with specific capacities. Following the unveiled model, a hybrid meta-heuristic algorithm will be devised that simultaneously takes advantage of a novel evaluation function, a clustering technique, and a genetic approach for solving the proposed model.</pre>

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Toward unraveling multi-objective optimization problems: A hybrid approach for solving a novel facility location problem

DehghanChenary¹,

Ferdowsi²,

Jolai³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Although facility location applications address mostly facility siting for product and service provision [37] [38], they have also been used for other non-location decisions. For instance, [39] presents a medical application where a double vision problem is formulated and solved as a p-median/p-center problem on a line.…”

Section: Case Study 2: Course Covering Modelmentioning

confidence: 99%

Planning and performance measurement in higher education: three case studies of operational research application

Villegas

Castañeda

Castañeda-Gómez

2021

Rev.Fac.Ing.Univ.Antioquia

View full text Add to dashboard Cite

In this work, we illustrate the application of a wide variety of Operations/operational research (OR) tools in higher education through three case studies based on practical applications conducted in the Engineering School of the Universidad de Antioquia. These case studies focus, respectively, on capacity planning, resource allocation, and performance measurement. In the first case study, we model and predict the flow of students enrolled in the industrial engineering program through the new curriculum using system dynamics and algebraic modeling of dropout rates, finding the number of sections for the courses, and the corresponding number of faculty positions needed to support the program structure. The second case study is a course covering model for the new curriculum that considers preferences and capacities of the teaching staff in an integer programming model, to find the uncovered courses of the new curriculum. Finally, the third case study presents a data envelopment analysis tool currently used to evaluate and rank the faculty of the Engineering School according to their teaching performance. The case studies presented in this work showcase how helpful OR tools are to rationalize the decision-making process in higher education institutions.

show abstract

“…In the operational research field, this issue is named facility location problem [7,8] and concerns the identification of facilities, so the costs incurred from allocating customers to the selected facilities are minimized, and represents nowadays a very active field of research. A recent survey on service facility location problems can be found in [5]. While this aspect has been widely explored at the level of managing resources in a cloud data center [1,12], it has not been considered so far in the fog computing field.…”

Section: Introductionmentioning

confidence: 99%

A Variable Neighborhood Heuristic for Facility Locations in Fog Computing

Queiroz¹,

Canali

Iori

et al. 2021

Variable Neighborhood Search

View full text Add to dashboard Cite

The current trend of the modern smart cities applications towards a continuous increase in the volume of produced data and the concurrent need for low and predictable latency in the response time has motivated the shift from a cloud to a fog computing approach. A fog computing architecture is likely to represent a preferable solution to reduce the application latency and the risk of network congestion by decreasing the volume of data transferred to cloud data centers. However, the design of a fog infrastructure opens new issues concerning not only how to allocate the data flow coming from sensors to fog nodes and from there to cloud data centers, but also the choice of the number and the location of the fog nodes to be activated among a list of potential candidates. We model this facility location issue through a multi-objective optimization problem. We propose a heuristic based on the variable neighborhood search, where neighborhood structures are based on swap and move operations. The proposed method is tested in a wide range of scenarios, considering a smart city application's realistic setup with geographically distributed sensors. The experimental evaluation shows that our method can achieve stable and better performance concerning other literature approaches, supporting the given application.

show abstract

A comparative survey of service facility location problems

Cited by 69 publications

References 151 publications

Toward unraveling multi-objective optimization problems: A hybrid approach for solving a novel facility location problem

Toward unraveling multi-objective optimization problems: A hybrid approach for solving a novel facility location problem

Planning and performance measurement in higher education: three case studies of operational research application

A Variable Neighborhood Heuristic for Facility Locations in Fog Computing

Contact Info

Product

Resources

About