Routing and scheduling decisions in the hierarchical hub location problem

Dükkancı, Okan; Kara, Bahar Y.

doi:10.1016/j.cor.2017.03.013

Cited by 49 publications

(35 citation statements)

References 32 publications

(36 reference statements)

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“…Random variables and fuzzy variables are the two most common ways of describing uncertainty. The objective function of this problem typically minimizes the costs of facility construction and transportation [24,[37][38][39][40].…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing Multimodal Transportation Routes Considering Container Use

et al. 2019

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This study focuses on the route selection problem of multimodal transportation: When facing a shortage of containers, a transport plan must be designed for freight forwarders that realizes the optimal balance between transportation time and transportation cost. This problem is complicated by two important characteristics: (1) The use of containers is related to transport routes, and they interact with each other; and (2) Different types of containers should be used in different time ranges for different modes of transportation. To solve this problem, we establish a multi-objective optimization model for minimizing the total transportation time, transportation cost and container usage cost. To solve the multi-objective programming model, the normalized normal constraint method (NNCM) is used to obtain Pareto solutions. We conducted a case study considering the transportation of iron ore in Panzhihua City, Sichuan Province. The results demonstrate that using railway containers and railway transportation as much as possible in route selection can effectively solve the problem of container shortage and balance transportation time and transportation cost.

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Section: Literature Reviewmentioning

confidence: 99%

Optimizing Multimodal Transportation Routes Considering Container Use

et al. 2019

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“…In contrast to the studies reported by Kim and O'Kelly [13] and An et al [11], the present study considers multi-level and multimodal dimensions of the problem to maximize reliability. A hierarchical multimodal hub covering network with a service time bound was proposed by Dukkanci and Kara [50], wherein three di erent types of a vehicle were considered at each level: airplanes, big trucks, and pickups. They proposed a heuristic algorithm for solving the problem on a Turkish network dataset.…”

Section: Multimodal Hub Locationmentioning

confidence: 99%

Reliable Hierarchical Multimodal Hub Location Problem: Models and Lagrangian Relaxation Algorithm

2018

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Hub facility location problems involve the establishment of strategic hub facilities and the allocation of demand nodes to them. Meanwhile, with the emergence of new transport and distribution networks with multi-level structures, the design of such networks has evolved. The diversity of transportation system has added multimodality to these problems. Considering the strategic nature and long-term implications of decisionmaking in this eld, the decisions shall be of high reliability. The present study is an attempt to consider the reliability of communication paths in proportion to the volume of transactions through them while covering all of the above-mentioned issues in hub location problems at the same time. Incorporating hierarchical characteristics of the problem into the model, one can obtain a signi cantly enhanced model in terms of multimodality and reliability. A Lagrangian solution method was developed considering the strategic level of the problem and the importance of the solution accuracy. The model was then validated in terms of time and quality.

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“…Constraints (16)- (22) represent integrality and non-negativity of variables. Although, it should be noted that redundant constraints (19) are considered to further strengthen the LP relaxation.…”

Section: Final Decision Variablesmentioning

confidence: 99%

“…They extend their work into multi-period model and solved the model using a variation of Adaptive clonal selection algorithm [18]. Also, recently Dükkanci and Kara [19] introduced a hierarchical multimodal hub covering problem whereas the upper level is configured by ring structure instead of star structure which is used in middle and lower levels. So, the routing and scheduling constraints are added to the model.…”

Section: Introductionmentioning

confidence: 99%

A bi-objective hierarchical hub location model with facility failure

et al. 2018

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In the most past hub location problem (HLP) studies, failure probability is limited to a constant value; while in reality, it depends on various factors including natural disasters such as floods and earthquakes, commodity flow, institutional elements such as strikes, and etc. This paper looks into the problem of hub network design through a new model. The problem is to maximize the network reliability and to minimize the total routing cost simultaneously. In order to provide a more realistic model, the hub's failure probabilities were considered as a function of the hub's incoming traffic. Reserve hub elements are also taken into account in the model with the aim of increasing network reliability. To solve the model, a non-dominated sorting genetic algorithm (NSGA-II) is presented. The parameters of the algorithm are tuned using Taguchi method. The proposed solution is then carried out in a case study where the results confirm the acceptable performance of the model and also sensitivity analysis is performed in order to describe the effects of critical parameters into objective functions.

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Routing and scheduling decisions in the hierarchical hub location problem

Cited by 49 publications

References 32 publications

Optimizing Multimodal Transportation Routes Considering Container Use

Optimizing Multimodal Transportation Routes Considering Container Use

Reliable Hierarchical Multimodal Hub Location Problem: Models and Lagrangian Relaxation Algorithm

A bi-objective hierarchical hub location model with facility failure

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