The uncapacitated hub location problem in networks under decentralized management

Vasconcelos, Adriano Dutra de; Nassi, Carlos David; Lopes, Luiz Antônio Silveira

doi:10.1016/j.cor.2011.03.004

Cited by 23 publications

(10 citation statements)

References 8 publications

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“…The exact methods include the Bender decomposition [40] and branch-and-bound [41]. The optimal solutions of the linear programming [42], integer programming [43], mixed integer programming [44] and quadratic programming [45] location problems can be obtained. The exact methods are suitable for the small-scale problems.…”

Section: Solution Methodsmentioning

confidence: 99%

Joint Distribution Center Location Problem for Restaurant Industry Based on Improved K-Means Algorithm With Penalty

et al. 2020

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The location of joint distribution center (JDC) is of great importance in urban freight system. This work aims to minimize the total cost, including the fixed cost, the transportation cost, and the penalty cost for the missed deliveries, considering the joint distribution willingness (JDW) of restaurant and the coverage radius of JDC. The integer programming model is formulated to select the optimal location of JDC and opens no more than k-JDCs. To solve the problem, an improved K-means (I-K-means) algorithm combining local search with penalty is proposed. The delivery problems obtained by freight survey from 114 restaurants in Beijing, China are taken as a case study. The formulation in this paper can reduce the cost of deliveries in restaurant industry, decrease the number of freight vehicles on road, and promote the joint distribution mode in urban freight system.

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Section: Solution Methodsmentioning

confidence: 99%

Joint Distribution Center Location Problem for Restaurant Industry Based on Improved K-Means Algorithm With Penalty

et al. 2020

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“…Alfandari et al [69] formulate the barge rotation problem with a MIP model to determine which terminal to visit and which container to transport. To reflect the different actors preference in choosing services in the network, Vasconcelos et al [70] use a Logit choice model to determine the proportion that a specific service is chosen. Meng and Wang [71] introduce user equilibrium constraints in their model.…”

Section: Methodologies Used In Itt Operationmentioning

confidence: 99%

Critical Literature Review into Planning of Inter-Terminal Transport: In Port Areas and the Hinterland

Corman

Lodewijks

2019

Journal of Advanced Transportation

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Nowadays, the major ports around the world usually consist of multiple terminals and service centers which are often run by different operators. Meanwhile, inland terminals have been also developed to reduce port congestion and improve transport efficiency. The integrated planning of inter-terminal transport (ITT) between the seaport and inland terminals helps in providing frequent and profitable services, but also could lead to higher overall planning complexity. Moreover, the ITT system usually involves multiple stakeholders with different or even conflicting interests. Although an increasing number of studies have been conducted in recent years, few studies have summarized the research findings and indicated the directions for future research regarding ITT. This paper provides a systemic review of ITT planning: we examine 77 scientific journal papers to identify what kind of objectives should be achieved in ITT system planning, which actors should be involved, and what methodologies can be used to support the decision-making process. Based on the analysis of the existing research, several research gaps can be found. For example, the multi-modality ITT systems are rarely studied; cooperation frameworks are needed in the coordination of different actors and quantitative methodologies should be developed to reflect the different actors’ financial interests.

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“…Single-stage problems deal with decisionmaking with no subsequent recourse. Vasconcelos et al [53] designed a hub network by using a decentralized management approach. In their model, the companies were chosen on the basis of the stochastic link cost of effective factors such as time and traffic.…”

Section: 2mentioning

confidence: 99%

Robust solution for a minimax regret hub location problem in a fuzzy-stochastic environment

Abbasi-Parizi¹,

Aminnayeri²,

Bashiri³

2018

Journal of Industrial &Amp; Management Optimization

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In the present paper, a robust approach is used to locate hub facilities considering network risks. An additional objective function, minimax regret, is added to the classical objective function in the hub location problem. In the proposed model, risk factors such as availability, security, delay time, environmental guidelines and regional air pollution are considered using triangular fuzzy-stochastic numbers. Then an equivalent crisp single objective model is proposed and solved by the Benders decomposition method. Finally, the results of both Benders decomposition and commercial optimization software are compared for different instances. Numerical instances were developed based on the well-known Civil Aeronautics Board (CAB) data set, considering different levels of uncertainty in parameters. The results show that the proposed model is capable of selecting nodes as sustainable hubs. Also, the results confirm that using Benders decomposition is more efficient than using classical solution methods for large-scale problems.

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The uncapacitated hub location problem in networks under decentralized management

Cited by 23 publications

References 8 publications

Joint Distribution Center Location Problem for Restaurant Industry Based on Improved K-Means Algorithm With Penalty

Joint Distribution Center Location Problem for Restaurant Industry Based on Improved K-Means Algorithm With Penalty

Critical Literature Review into Planning of Inter-Terminal Transport: In Port Areas and the Hinterland

Robust solution for a minimax regret hub location problem in a fuzzy-stochastic environment

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