Robust optimization approach to the design of hub-and-spoke networks

Ghaffarinasab, Nader; Ghazanfari, Mehdi; Teimoury, Ebrahim

doi:10.1007/s00170-014-6330-5

Cited by 44 publications

(14 citation statements)

References 24 publications

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“…However, to the best of our knowledge there was no published research studies on the investigation of uncertainty impacts on real hub location problems with capacity constraints and inaccurate decision parameters. This research study fulfills a needed gap on capacitated HLP under uncertainty as suggested for future research by many recent research studies Alumur et al (2012), Adibi & Razmi (2015), Ghaffari-Nasab et al (2015). In this study, a novel mathematical model is proposed to question this hypothesis whether deterministic modeling and seasonal optimization can be sound measures for obtaining the optimal location of the hubs under different sources of uncertainty.…”

Section: Our Contributionmentioning

confidence: 87%

Hub location under uncertainty: a minimax regret model for the capacitated problem with multiple allocations

Kazemian

Aref

2017

IJSCIM

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Abstract:In this paper the capacitated hub location problem is formulated by a minimax regret model, which takes into account uncertain setup cost and demand. We focus on hub location with multiple allocations as a strategic problem requiring one definite solution.Investigating how deterministic models may lead to sub-optimal solutions, we provide an efficient formulation method for the problem.A computational analysis is performed to investigate the impact of uncertainty on the location of hubs. The suggested model is also compared with an alternative method, seasonal optimization, in terms of efficiency and practicability. The results indicate the importance of incorporating stochasticity and variability of parameters in solving practical hub location problems. Applying our method to a case study derived from an industrial food production company, we solve a logistical problem involving seasonal demand and uncertainty. The solution yields a definite hub network configuration to be implemented throughout the planning horizon.

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Section: Our Contributionmentioning

confidence: 87%

Hub location under uncertainty: a minimax regret model for the capacitated problem with multiple allocations

Kazemian

Aref

2017

IJSCIM

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“…Nikoofal and Sadjadi [13] used Bertimas and Sim's approach [5] to propose the robust model of the median hub location problem with uncertain travel cost. Taking advantage of Bertsimas and Sim's approach [5], Ghaffari-Nasab et al [14] proposed a robust model for the capacitated hub location problem (single allocationmultiple allocation) in which the demand change was uncertain. They used uncertain demand only for capacity constraints and supposed that the objective function of demand is certain.…”

Section: Literature Reviewmentioning

confidence: 99%

Development of a Model for Locating Hubs in a Competitive Environment under Uncertainty: A Robust Optimization Approach

Nourzadeh

Ebrahimnejad

Khalili‐Damghani

et al. 2020

IJE

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This article explores the development of previous models to determine hubs in a competitive environment. In this paper, by comparing parameters of the ticket price, travel time and the service quality of hub airports, airline hubs are divided into six categories. The degree of importance of travel time and travel cost are determined by a multivariate Lagrange interpolation method, which can play an important role in allocating travelers to follower airline hubs. Then, based on the seasonal demand of travelers, we consider travel demand as uncertain parameters. To determine the robust counterpart of this category of hub location models, a robust optimization method is used. Finally, models are tested in a case study. The central results show that the follower airline's income has a considerable growth and can absorb nearly 2% of travelers of the leader airline due to lower travel costs and travel time compared to that of leader airline.

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“…In this eld, there are three main directions: (1) Research on the construction of regional logistics network and its in uencing factors. For example, based on the perspective of optimal cost and value risk, domestic and foreign scholars put forward the design method of spoke structure network, as well as the delivery routes and scheduling of hub nodes [1][2][3][4]; or take a certain area as an actual case to study the positioning of logistics center in logistics transportation network [5][6][7]; or study the impact of system and policy on the construction of logistics network in coastal cities under similar conditions of natural environment and other characteristics [8][9][10]. (2) Research on the construction and optimization of regional logistics network.…”

Section: Introductionmentioning

confidence: 99%

Research on the Supernetwork Equalization Model of Multilayer Attributive Regional Logistics Integration

Yanna

Xin

et al. 2019

Discrete Dynamics in Nature and Society

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Based on the multi-level structure attributes of regional logistics, regional logistics integration presents complex features. Therefore, according to the operational requirements of regional logistics integration, we built a regional logistics network structure model consisting of infrastructure, information resources, and organizational networks; selected the level of relationship between different layers and information dissemination, and transport flow as decision variables. We built a supernetwork mathematical model of regional logistics integration with multiple layers of attributes. Considering the constraints of marginal cost changes and overall revenue, we found an equilibrium solution for the operation of regional logistics integration supernetwork. That is, the optimal match between the level of relationship, the level of information dissemination and the transportation flow, provides a reference basis for the formulation of relevant policies and implementation strategies.

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Robust optimization approach to the design of hub-and-spoke networks

Cited by 44 publications

References 24 publications

Hub location under uncertainty: a minimax regret model for the capacitated problem with multiple allocations

Hub location under uncertainty: a minimax regret model for the capacitated problem with multiple allocations

Development of a Model for Locating Hubs in a Competitive Environment under Uncertainty: A Robust Optimization Approach

Research on the Supernetwork Equalization Model of Multilayer Attributive Regional Logistics Integration

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