On tabu search for the location of interacting hub facilities

Skorin-Kapov, Darko; Skorin-Kapov, Jadranka

doi:10.1016/0377-2217(94)90245-3

Cited by 203 publications

(80 citation statements)

References 5 publications

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“…Using their method, the authors showed that the tabu search method of Skorin-Kapov and Skorin-Kapov (1994) was within an average gap of 3.3% for smaller problems (10-15 nodes) and an average gap of 5.9% for the 20 and 25 node problems. Later, with the optimal solutions to the CAB data set SkorinKapov et al (1996) were able to validate the optimality of the tabu search solutions obtained in Skorin-Kapov and Skorin-Kapov (1994).…”

Section: ðSkorin-kapov Et Al:; 1996þ Minmentioning

confidence: 99%

Network hub location problems: The state of the art

Alumur

Kara

2008

European Journal of Operational Research

763

338

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Hubs are special facilities that serve as switching, transshipment and sorting points in many-to-many distribution systems. The hub location problem is concerned with locating hub facilities and allocating demand nodes to hubs in order to route the traffic between origin-destination pairs. In this paper we classify and survey network hub location models. We also include some recent trends on hub location and provide a synthesis of the literature.

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Section: ðSkorin-kapov Et Al:; 1996þ Minmentioning

confidence: 99%

Network hub location problems: The state of the art

Alumur

Kara

2008

European Journal of Operational Research

763

338

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“…The earlier heuristics are as follows: O'Kelly [9] proposes two heuristics based on the enumeration of p hub locations; Klincewicz [14], [15] develop an exchange heuristic, a GRASP (Greedy Randomized Search Procedure) and a tabu search heuristic; Skorin-Kapov [16] also provides a tabu search heuristic. O'Kelly [17] presents a lower bounding technique based on linerization of the quadratic objective function.…”

Section: P-hub Median Problemsmentioning

confidence: 99%

The hub location and routing problem

Bayraktar¹

1996

Location Science

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Hubs are special facilities that consolidate and disseminate flows in many-to-many distribution systems. The hub location problem aims to find locations of hubs and allocate non-hub nodes directly to the hubs. However, this problem is necessary to extend when nodes do not have sufficient demand to justify direct connections between the non-hub nodes to the hubs since such direct connections increase the number of vehicles required and decrease the utilization of vehicles. Hence, it is necessary to construct local tours among the nodes allocated to the same hubs to generate economies of scale and to decrease vehicle costs. Nevertheless, forcing each non-hub node to be visited by a local tour is not the best way to design a many-to-many distribution system. Therefore, in this study two options for each non-hub node are given: (i) either it could be visited by a local tour or (ii) it could be directly connected to a hub without an economy of scale. We develop a mixed integer programming formulation and strengthen it with valid inequalities. We also develop three different Benders formulations as exact solution methods. In addition, we develop a hierarchical heuristic with two phases in order to solve large-sized problem instances. We test the performances of our solution methodologies on CAB and TR data sets. Anahtar sözcükler : ADÜ yer seçimi, rotalama, Benders ayrıştırma yöntemi. Keywordsiv

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“…In early studies for hub location problems, researchers applied different solution methods for solving them. For instance, [21] proposed a heuristic method based on tabu search (TS) for solving single allocation problems. Reference [22] proposed a new linear formulation for single allocation model with fewer variables and constraints than the classical formulations.…”

Section: Introductionmentioning

confidence: 99%

Finding p-Hub Median Locations: An Empirical Study on Problems and Solution Techniques

Sun

Dai

Zhang

et al. 2017

Journal of Advanced Transportation

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Hub location problems have been studied by many researchers for almost 30 years, and, accordingly, various solution methods have been proposed. In this paper, we implement and evaluate several widely used methods for solving five standard hub location problems. To assess the scalability and solution qualities of these methods, three well-known datasets are used as case studies: Turkish Postal System, Australia Post, and Civil Aeronautics Board. Classical problems in small networks can be solved efficiently using CPLEX because of their low complexity. Genetic algorithms perform well for solving three types of single allocation problems, since the problem formulations can be neatly encoded with chromosomes of reasonable size. Lagrangian relaxation is the only technique that solves reliable multiple allocation problems in large networks. We believe that our work helps other researchers to get an overview on the best solution techniques for the problems investigated in our study and also stipulates further interest on cross-comparing solution techniques for more expressive problem formulations.

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On tabu search for the location of interacting hub facilities

Cited by 203 publications

References 5 publications

Network hub location problems: The state of the art

Network hub location problems: The state of the art

The hub location and routing problem

Finding p-Hub Median Locations: An Empirical Study on Problems and Solution Techniques

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