Hub location problems: A review of models, classification, solution techniques, and applications

Farahani, Reza Zanjirani; Hekmatfar, Masoud; Arabani, Alireza Boloori; Nikbakhsh, Ehsan

doi:10.1016/j.cie.2013.01.012

Cited by 459 publications

(198 citation statements)

References 143 publications

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“…The literature on hub location problems has increased significantly in the last years as can be observed in the survey paper by Alamur and Kara [27] Also, Farahani et al [28] reviewed multi-criteria approaches to hub location problems. Next, Farahani et al [29] focuses on reviewing the most recent hub location problems from 2007 up to 2012. The problem of hub location has attracted many researchers.…”

Section: Overview Of Research On Dry Port Locationmentioning

confidence: 99%

Dry Port Location Problem: A Hybrid Multi-Criteria Approach

Bentaleb¹,

Mabrouki²,

Semma³

2016

J ETA Maritime Sci

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Section: Overview Of Research On Dry Port Locationmentioning

confidence: 99%

Dry Port Location Problem: A Hybrid Multi-Criteria Approach

Bentaleb¹,

Mabrouki²,

Semma³

2016

J ETA Maritime Sci

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“…They also explored the shortcomings of the literature and suggested future research directions. A short after, Farahani et al (2013) provided a latest review of models, classification, solution techniques and applications of hub location problems. To provide a concise overview of the literature review, the paramount feature of each studies mentioned above are encapsulated in Table 1.…”

Section: Fig 1 a Single Allocation (Left Hand Side) And Multiple Almentioning

confidence: 99%

“…2013 (Bashiri et al, 2013) A fuzzy capacitated p-hub center problem is introduced and a genetic algorithm solution is presented. 2013 (Farahani et al, 2013) A comprehensive survey of hub location problems is presented. 2013 (Liang, 2013) The hardness of star p-hub center is analyzed.…”

Section: Fig 1 a Single Allocation (Left Hand Side) And Multiple Almentioning

confidence: 99%

Solving uncapacitated multiple allocation p-hub center problem by Dijkstra’s algorithm-based genetic algorithm and simulated annealing

Rabbani¹,

Kazemi²

2015

10.5267/j.ijiec

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In the existing literature, there are a huge number of studies focused on p-hub median problems and inventing heuristic or metaheuristic algorithms for solving them. But such analogous body of literature does not exist for its counterpart problem; p-hub center problem. In fact, since p-hub center has been lately introduced and has a particular objective function, minimizing the maximum cost between origin-destination nodes, there are few studies investigating the problem and the challenges for solving it. In this study, after presenting a complete definition of the uncapacitated multiple allocation p-hub center problem (UMApHCP) two well-known metaheuristic algorithms are proposed to solve the problem for small scale and large scale standard data sets. These two algorithms are one single solution-based algorithm, Simulated Annealing (SA), and one population-based metaheuristic, Genetic Algorithm (GA). Because of the particular nature of the problem, Dijkstra's algorithm has been incorporated in the fitness function calculation part of the proposed methods. The numerical results of running the GA and SA for standard test problems show that for smaller scale test problems, single solution-based SA shows greater performance versus GA but for larger scales of data sets the GA generally yield more desirable solutions.

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“…Many different types of HLP were introduced by Campbell [14], such as phub median, p-hub center and p-hub covering. For more detailed information in this field [19], [20] are comprehensive review, in which most of the readers are referred to them.…”

Section: Literature Reviewmentioning

confidence: 99%

An Efficient Imperialism Competitive Algorithm for a Reliable Hub Covering Location Problem

Sadeghi¹,

Tavakkoli‐Moghaddam²

2015

IJMLC

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Abstract-Hubs are critical elements that benefit networks by switching, distributing and concentrating flows. A hub location problem is common in a lot of industries, such as transportation networks, telecommunication networks, postal delivery networks and express shipment. Furthermore, a transportation network plays a vital role in each country. Nonetheless, during a day many factors such as traffic incidence, natural disasters cause some degradation in the transportation network. As a result, in this paper, we study a reliable hub covering location problem in a degradable transportation network to minimize the total transportation cost. For achieving near-optimal solutions for a real-sized problem an imperialism competitive algorithm (ICA) is proposed. Also the effectiveness of the proposed ICA is shown by some computational experiments. At last, conclusion is provided.

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Hub location problems: A review of models, classification, solution techniques, and applications

Cited by 459 publications

References 143 publications

Dry Port Location Problem: A Hybrid Multi-Criteria Approach

Dry Port Location Problem: A Hybrid Multi-Criteria Approach

Solving uncapacitated multiple allocation p-hub center problem by Dijkstra’s algorithm-based genetic algorithm and simulated annealing

An Efficient Imperialism Competitive Algorithm for a Reliable Hub Covering Location Problem

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