Multicriteria hub decision making for rural area telecommunication networks

Lee, Heeseok; Shi, Yong; Nazem, Sufi M.; Kang, Sung Yeol; Park, Tae Ho; Sohn, Myung Ho

doi:10.1016/s0377-2217(00)00191-0

Cited by 15 publications

(6 citation statements)

References 15 publications

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“…The variation of the hub allocation problem is capacitated single allocation p-hub median problem (CSApHMP). This field assumes different ways of capacities introduction in the model: capacities on flow into hub or total flow [10], the minimum flow value is needed to allow link between nonhub node and hub [11]. The hub locations problem applications in postal delivery services, emergency services and logistic systems [12][13][14].…”

Section: таблmentioning

confidence: 99%

Single hub location-allocation problem under robustness clustering concept

Lozkins¹,

Bure²

2017

Vestnik SPbSU. Applied Mathematics. Computer Science. Control P

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This paper presents an algorithm of hub number p robustness estimation using specific simulations in the single allocation hub location problem. The simulation has to model the service demand trends in each origin node to each destination node. This idea is based on the hub network dependence on service demand forecasting, which is modeled by random values from random distribution with parameters reflecting the demand changes. The algorithm includes the mixed integer programming model which describes the hub location-allocation problem with single allocation (each node is connected exactly to one hub). The model chooses the optimal locations for the fixed number of hubs p from the fixed possible location set in the problem. The perturbed data simulate the changes in the service need and present the perspectives of the network changes, and the algorithm fixes these changes. The number of changes in the network is consolidated into the variety frequencies which describe the variabilities in the set of simulations. The algorithm is implemented on Python 3.5 and model optimization is fulfilled using Gurobi Optimizer 7.0.1 software. The results in the real dataset are illustrated and discussed. Refs 18. Fig. 1. Tables 3.

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Section: таблmentioning

confidence: 99%

Single hub location-allocation problem under robustness clustering concept

Lozkins¹,

Bure²

2017

Vestnik SPbSU. Applied Mathematics. Computer Science. Control P

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“…The problem of designing a telecommunications network over a given geographically dispersed area is an important practical problem that involves engineering and economic aspects (see Kawasumi et al 2007;Lee et al 2001;Nazem et al 1994). Most efforts undertaken along these lines resort to binary mathematical programming.…”

Section: Introductionmentioning

confidence: 99%

Optimum acceptability of telecommunications networks: a multi-criteria approach

et al. 2018

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This paper proposes an aggregated index of acceptability that can establish a "ranking" of the possible candidate hub cities in the design of a telecommunications network. The main advantages of the aggregated index proposed are the following: (a) it takes into account several wide-ranging design criteria, (b) its formulation is given by a lineal mathematical expression, (c) the procedure for calculating the index is very simple, and (d) the candidate hubs can be ranked differently depending on the aggregation structure of the criteria involved. Taking this considerations, the application of the proposed methodology can supplement the information supplied by more sophisticated multicriteria approaches based generally upon 0/1 goal programming. The theory presented is illustrated using a case study taken from the literature.

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“…There are many variants about this issue: non-hub nodes may be allocated only to one hub-single allocation, Ernst [1,2], O'Kelly [3] or to several hubs-multiple allocation, Ernst [4]; the use of direct links between non-hub nodes may be allowed; the location of some (or all) hubs may be fixed; hub nodes may be allowed to be located anywhere in a continuous region-continuous hub location problems, O'Kelly [5] or may be chosen from a discrete set of places-discrete hub location problems; there may exist a constraint fixing the number of nodes that will be selected as hubs-p-hub problem, Klincewicz [6], Skorin-Kapov [7], or a fixed cost for establishing a hub may be considered; instead of choosing nodes to locate hubs, we can select the arcs connecting the non-hub nodes to hubs-hub arc location problem, Campbell [8,9]. Capacities in hub location problems may assume different aspects: there can be capacities on the hub nodes (limiting the volume of flow into the hub, Ebery [10], Ernst [11], Aykin [12] or for the total flow through the hub) as well as on the flows between hubs or between hubs and non-hubs; on other hand, a minimum flow value needed to allow service on the link between a non-hub node and a hub may exist, Lee [13], Skorin-Kapov [14]. Many different cost functions have been studied, for example, flow-dependent cost functions, O'Kelly [15]; time functions-latest arrival hub location problem, Kara [16].…”

Section: Introductionmentioning

confidence: 99%

Capacitated Location-Allocation Hub Covering Problem in Manufacturing-Customer Interaction

Fazlollahtabar¹

2015

J Appl Computat Math

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This paper presents a location-allocation hub covering considering capacity constraints for multiple hubs and allocates non-hub nodes including the manufacturer and the customer. The model is an integer linear programming minimizing the transfer costs and optimizes the allocation requests from the manufacturer to the customer passing through one or two hubs. It also simultaneously minimize the cost allocation requests and optimize the use of any existing network hub and the use of any existing network hub due to restrictions on the transfer or collect applications to hub. The model optimization is fulfilled using Lingo 9.0 software, and a discussion is comprehensibly illustrating the aspects of the proposed model.

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Multicriteria hub decision making for rural area telecommunication networks

Cited by 15 publications

References 15 publications

Single hub location-allocation problem under robustness clustering concept

Single hub location-allocation problem under robustness clustering concept

Optimum acceptability of telecommunications networks: a multi-criteria approach

Capacitated Location-Allocation Hub Covering Problem in Manufacturing-Customer Interaction

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