scholarly journals A Biobjective and Trilevel Programming Model for Hub Location Problem in Design of a Resilient Power Projection Network

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Hai-Ling Bi ◽  
Kai Kang ◽  
Xu-Tao Zhang
Keyword(s):  
Programming Model ◽  
Multiple Criteria Decision Making ◽  
Complex Model ◽  
Hub Location ◽  
Hub Location Problem ◽  
Worst Case ◽  
Power Projection ◽  
Network Cost ◽  
The Cost ◽  
Projection Network

Hubs disruptions are taken into account in design of a resilient power projection network. The problem is tackled from a multiple criteria decision-making (MCDM) perspective. Not only the network cost in normal state is considered, but also the cost in the worst-case situation is taken into account. A biobjective and trilevel integer programming model is proposed using game theory. Moreover, we develop a metaheuristic based on tabu search and shortest path algorithm for the resolution of the complex model. Computational example indicates that making tradeoffs between the performances of the network in different situations is helpful for designing a resilient network.

scholarly journals A Stochastic Programming Approach for Resilient Hub Location in Power Projection Network considering Random Hub Failures

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xu-Tao Zhang ◽  
Hai-Ling Bi ◽  
Yun Wang
Keyword(s):  
Stochastic Programming ◽  
Programming Model ◽  
Programming Approach ◽  
Hub Location ◽  
Hub Location Problem ◽  
Power Projection ◽  
Critical Facilities ◽  
Resilient Networks ◽  
The Impact ◽  
Projection Network

Hubs are critical facilities in the power projection network. Due to the uncertainty factors such as terrorism threats, severe weather, and natural disasters, hub facilities may be disrupted randomly, which could lead to excessive cost or loss in practice. One of the most effective ways to withstand and reduce the impact of disruptions is designing more resilient networks. In this paper, a stochastic programming model is employed for the hub location problem in the presence of random hub failures. A heuristic algorithm based on Monte Carlo method and tabu search is put forward to solve the model. The proposed approach is more general if there are numbers of hubs that would fail even with different failure probability. Compared with the benchmark model, the model which takes the factor of stochastic failure of hubs into account can give a more resilient power projection network.

scholarly journals Location of regional and international hub ports in liner shipping

2017 ◽  
Vol 2 (2) ◽  
pp. 114-125 ◽  
Author(s):  
Jianfeng Zheng ◽  
Cong Fu ◽  
Haibo Kuang
Keyword(s):  
Design Methodology ◽  
Location Problem ◽  
Programming Model ◽  
Liner Shipping ◽  
Mixed Integer ◽  
Eastern Asia ◽  
Hub Location ◽  
Hub Location Problem ◽  
Content Type ◽  
Western Asia

Purpose This paper aims to investigate the location of regional and international hub ports in liner shipping by proposing a hierarchical hub location problem. Design/methodology/approach This paper develops a mixed-integer linear programming model for the authors’ proposed problem. Numerical experiments based on a realistic Asia-Europe-Oceania liner shipping network are carried out to account for the effectiveness of this model. Findings The results show that one international hub port (i.e. Rotterdam) and one regional hub port (i.e. Zeebrugge) are opened in Europe. Two international hub ports (i.e. Sokhna and Salalah) are located in Western Asia, where no regional hub port is established. One international hub port (i.e. Colombo) and one regional hub port (i.e. Cochin) are opened in Southern Asia. One international hub port (i.e. Singapore) and one regional hub port (i.e. Jakarta) are opened in Southeastern Asia and Australia. Three international hub ports (i.e. Hong Kong, Shanghai and Yokohama) and two regional hub ports (i.e. Qingdao and Kwangyang) are opened in Eastern Asia. Originality/value This paper proposes a hierarchical hub location problem, in which the authors distinguish between regional and international hub ports in liner shipping. Moreover, scale economies in ship size are considered. Furthermore, the proposed problem introduces the main ports.

scholarly journals Megaregional Passenger Transportation Hub Location Problem Considering Congestion Effects

2021 ◽  
Vol 33 (4) ◽  
pp. 551-563
Author(s):  
Huang Yan ◽  
Xiaoning Zhang
Keyword(s):  
Location Problem ◽  
Travel Demand ◽  
Programming Model ◽  
Transportation Network ◽  
Network Capacity ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Passenger Transportation ◽  
Congestion Effects

The need to make effective plans for locating transportation hubs is of increasing importance in the megaregional area, as recent research suggests that the growing intercity travel demand affects the efficiency of a megaregional transportation system. This paper investigates a hierarchical facility location problem in a megaregional passenger transportation network. The aim of the study is to determine the locations of hub facilities at different hierarchical levels and distribute the demands to these facilities with minimum total cost, including investment, transportation, and congestion costs. The problem is formulated as a mixed-integer nonlinear programming model considering the service availability structure and hub congestion effects. A case study is designed to demonstrate the effectiveness of the proposed model in the Wuhan metropolitan area. The results show that the congestion effects can be addressed by reallocating the demand to balance the hub utilisation or constructing new hubs to increase the network capacity. The methods of appropriately locating hubs and distributing traffic flows are proposed to optimise the megaregional passenger transportation networks, which has important implications for decision makers.

Distributionally Robust Hub Location

2020 ◽  
Vol 54 (5) ◽  
pp. 1189-1210 ◽  
Author(s):  
Shuming Wang ◽  
Zhi Chen ◽  
Tianqi Liu
Keyword(s):  
Convex Hull ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Mixed Integer Linear Program ◽  
Worst Case ◽  
Data Set ◽  
Second Stage ◽  
Robust Model ◽  
Distributionally Robust

We study the adaptive distributionally robust hub location problem with multiple commodities under demand and cost uncertainty in both uncapacitated and capacitated cases. The hub location decision anticipates the worst-case expected cost over an ambiguity set of possible distributions of the uncertain demand and cost, and the routing policy, being adaptive to the uncertainty realization, ships commodities through selected hubs. We investigate the adaptivity and tractability of the distributionally robust model under different distributional information about uncertainty. In the uncapacitated case in which demand and cost are independent and costs of different commodities are also mutually independent, the adaptive distributionally robust model is equivalent to a nonadaptive classical robust model and the second-stage routing decision follows an optimal static policy. We then relax the independence assumption and show that the second-stage routing decision follows an optimal scenario-wise policy if either the demand or the cost is supported on a convex hull of given scenarios. We extend our analysis to the capacitated case and show that the second-stage routing decision still follows an optimal scenario-wise policy if the demand is supported on the convex hull of given scenarios. In terms of tractability, for all mentioned cases, we reformulate the distributionally robust model as a moderate-sized mixed-integer linear program, and we recover the associated worst-case distribution by solving a collection of linear programs. Through numerical studies using the Civil Aeronautics Board data set, we demonstrate the advantages of the distributionally robust model by examining its superior out-of-sample performance against the classical robust model and the stochastic model.

An Optimal Design for the Capacitated Hub Location Problem with Asymmetric Allocation

2013 ◽  
Vol 284-287 ◽  
pp. 1203-1207
Author(s):  
Ji Ung Sun
Keyword(s):  
Solution Method ◽  
Location Problem ◽  
Programming Model ◽  
Service Level ◽  
Transportation Costs ◽  
Ant Colony Optimization Algorithm ◽  
Hub Location ◽  
Hub Location Problem ◽  
Hub And Spoke ◽  
Pass Through

Hub and Spoke (H&S) network reflecting the scale economies through consolidation and a large amount of freight transportation is widely used to reduce total transportation costs. H&S network has transportation routes that go to the final delivery point pass through hub linking destination from hub linking origin. In this paper we present a 0-1 integer programming model and a solution method for the capacitated asymmetric allocation hub location problem (CAAHLP). We determine the number of hubs, the locations of hubs, and asymmetric allocation of non-hub nodes to hub with the objective of minimum total transportation costs satisfying the required service level. As the CAAHLP has impractically demanding for the large sized problem, we develop a solution method based on ant colony optimization algorithm. We investigate performance of the proposed solution method through the comparative study. The experimental results show that the newly proposed asymmetrically allocated network can provide better solution than the singly allocated network in terms of cost and service level.

scholarly journals An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ji Ung Sun
Keyword(s):  
Evolutionary Algorithm ◽  
Vehicle Routing ◽  
Solution Method ◽  
Programming Model ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

We consider a capacitated hub location-routing problem (HLRP) which combines the hub location problem and multihub vehicle routing decisions. The HLRP not only determines the locations of the capacitatedp-hubs within a set of potential hubs but also deals with the routes of the vehicles to meet the demands of customers. This problem is formulated as a 0-1 mixed integer programming model with the objective of the minimum total cost including routing cost, fixed hub cost, and fixed vehicle cost. As the HLRP has impractically demanding for the large sized problems, we develop a solution method based on the endosymbiotic evolutionary algorithm (EEA) which solves hub location and vehicle routing problem simultaneously. The performance of the proposed algorithm is examined through a comparative study. The experimental results show that the proposed EEA can be a viable solution method for the supply chain network planning.

scholarly journals Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Sen Liu ◽  
Zhilan Song ◽  
Shuqi Zhong
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Public Transportation ◽  
Group Decision ◽  
Numerical Study ◽  
Hub Location ◽  
Hub Location Problem ◽  
The Public ◽  
Multiple Attribute ◽  
Qualitative Factors

Urban public transportation hubs are the key nodes of the public transportation system. The location of such hubs is a combinatorial problem. Many factors can affect the decision-making of location, including both quantitative and qualitative factors; however, most current research focuses solely on either the quantitative or the qualitative factors. Little has been done to combine these two approaches. To fulfill this gap in the research, this paper proposes a novel approach to the public transportation hub location problem, which takes both quantitative and qualitative factors into account. In this paper, an improved multiple attribute group decision-making (MAGDM) method based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and deviation is proposed to convert the qualitative factors of each hub into quantitative evaluation values. A location model with stochastic passenger flows is then established based on the above evaluation values. Finally, stochastic programming theory is applied to solve the model and to determine the location result. A numerical study shows that this approach is applicable and effective.

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