scholarly journals Hierarchical Passenger Hub Location Problem in a Megaregion Area Considering Service Availability

2021 ◽  
Vol 33 (2) ◽  
pp. 247-258
Author(s):  
Huang Yan ◽  
Xiaoning Zhang ◽  
Xiaolei Wang
Keyword(s):  
Travel Demand ◽  
Transportation Network ◽  
Mixed Integer ◽  
Service Availability ◽  
Hub Location ◽  
Hub Location Problem ◽  
Passenger Transportation ◽  
Linear Programming Formulation ◽  
Wuhan Metropolitan Area ◽  
The Impact

The rapid growth of the intercity travel demand has resulted in enormous pressure on the passenger transportation network in a megaregion area. Optimally locating hubs and allocating demands to hubs influence the effectiveness of a passenger transportation network. This study develops a hierarchical passenger hub location model considering the service availability of hierarchical hubs. A mixed integer linear programming formulation was developed to minimize the total cost of hub operation and transportation for multiple travel demands and determine the proportion of passengers that access hubs at each level. This model was implemented for the Wuhan metropolitan area in four different scenarios to illustrate the applicability of the model. Then, a sensitivity analysis was performed to assess the impact of changing key parameters on the model results. The results are compared to those of traditional models, and the findings demonstrate the importance of considering hub choice behavior in demand allocation.

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.

scholarly journals A P-Hub Location Problem for Determining Park-and-Ride Facility Locations with the Weibit-Based Choice Model

2021 ◽  
Vol 13 (14) ◽  
pp. 7928
Author(s):  
Songyot Kitthamkesorn ◽  
Anthony Chen ◽  
Sathaporn Opasanon ◽  
Suwicha Jaita
Keyword(s):  
Public Transportation ◽  
Choice Model ◽  
Transportation Network ◽  
Transportation Systems ◽  
Mixed Integer ◽  
Hub Location ◽  
Hub Location Problem ◽  
Facility Locations ◽  
Park And Ride ◽  
Public Transportation Systems

Park and ride (P&R) facilities provide intermodal transfer between private vehicles and public transportation systems to alleviate urban congestion. This study developed a mathematical programming formulation for determining P&R facility locations. A recently developed Weibit-based model was adopted to represent the traveler choice behavior with heterogeneity. The model’s independence of irrelevant alternatives (IIA) property was explored and used to linearize its nonlinear probability. Some numerical examples are provided to demonstrate a feature of the proposed mixed integer linear programing (MILP). The results indicate a significant impact of route-specific perception variance on the optimal P&R facility locations in a real-size transportation 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 KGPMH: A hybrid approach for solving a novel facility location problem

2021 ◽  
Author(s):  
Maryam DehghanChenary ◽  
Arman Ferdowsi ◽  
Fariborz Jolai ◽  
Reza Tavakkoli-Moghaddam
Keyword(s):  
Mathematical Model ◽  
Location Problem ◽  
Hybrid Approach ◽  
Facility Location Problem ◽  
Evaluation Function ◽  
Genetic Approach ◽  
Hub Location ◽  
Hub Location Problem ◽  
Proposed Model ◽  
The Impact

<pre>The focus of this paper is to propose a bi-objective mathematical model for a new extension of a multi-period p-mobile hub location problem and then to devise an algorithm for solving it. The developed model considers the impact of the time spent traveling at the hubs' network, the time spent at hubs for processing the flows, and the delay caused by congestion at hubs with specific capacities. Following the unveiled model, a hybrid meta-heuristic algorithm will be devised that simultaneously takes advantage of a novel evaluation function, a clustering technique, and a genetic approach for solving the proposed model.</pre>

scholarly journals Hub location problem in round-trip service applications

2020 ◽  
Author(s):  
Omar Kemmar ◽  
Karim Bouamrane ◽  
Shahin Gelareh
Keyword(s):  
Economies Of Scale ◽  
Location Problem ◽  
Service Providers ◽  
Real Life ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Hub Location ◽  
Service Networks ◽  
Hub Location Problem ◽  
Hub And Spoke

In this paper, we introduce a new hub-and-spoke structure for service networks based on round-trips as practiced by some transport service providers. This problem is a variant of Uncapacitated Hub Location Problem wherein the spoke nodes allocated to a hub node form round-trips (cycles) starting from and ending to the hub node. This problem is motivated by two real-life practices in logistics wherein  runaway  nodes and  runaway  connections with their associated economies of scale were foreseen to increase redundancy in the network. We propose a mixed integer linear programming mathematical model with exponential number of constraints. In addition to the separation routines for separating from among exponential constraints, we propose a hyper-heuristic based on reinforcement learning and its comparable counterpart as a variable neighborhood search. Our extensive computational experiments confirm efficiency of the proposed approaches.In this paper, we introduce a new hub-and-spoke structure for service networks based on round-trips as practiced by some transport service providers. This problem is a variant of Uncapacitated Hub Location Problem wherein the spoke nodes allocated to a hub node form round-trips (cycles) starting from and ending to the hub node. This problem is motivated by two real-life practices in logistics wherein  runaway  nodes and  runaway  connections with their associated economies of scale were foreseen to increase redundancy in the network. We propose a mixed integer linear programming mathematical model with exponential number of constraints. In addition to the separation routines for separating from among exponential constraints, we propose a hyper-heuristic based on reinforcement learning and its comparable counterpart as a variable neighborhood search. Our extensive computational experiments confirm efficiency of the proposed approaches.

scholarly journals Bi-objective load balancing multiple allocation hub location: a compromise programming approach

2020 ◽  
Vol 296 (1-2) ◽  
pp. 363-406 ◽  
Author(s):  
Rahimeh Neamatian Monemi ◽  
Shahin Gelareh ◽  
Anass Nagih ◽  
Dylan Jones
Keyword(s):  
Spatial Distribution ◽  
Transportation Cost ◽  
Compromise Programming ◽  
Mixed Integer ◽  
Programming Approach ◽  
Hub Location ◽  
Hub And Spoke ◽  
Classical Models ◽  
Linear Programming Formulation ◽  
Multiple Allocation

AbstractIn this paper we address unbalanced spatial distribution of hub-level flows in an optimal hub-and-spoke network structure of median-type models. Our study is based on a rather general variant of the multiple allocation hub location problems with fixed setup costs for hub nodes and hub edges in both capacitated and uncapacitated variants wherein the number of hub nodes traversed along origin-destination pairs is not constrained to one or two as in the classical models.. From the perspective of an infrastructure owner, we want to make sure that there exists a choice of design for the hub-level sub-network (hubs and hub edges) that considers both objectives of minimizing cost of transportation and balancing spatial distribution of flow across the hub-level network. We propose a bi-objective (transportation cost and hub-level flow variance) mixed integer non-linear programming formulation and handle the bi-objective model via a compromise programming framework. We exploit the structure of the problem and propose a second-order conic reformulation of the model along with a very efficient matheuristics algorithm for larger size instances.

scholarly journals Optimization of the Collaborative Hub Location Problem with Metaheuristics

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2759
Author(s):  
Gargouri Mohamed Amine ◽  
Hamani Nadia ◽  
Mrabti Nassim ◽  
Kermad Lyes
Keyword(s):  
Distribution Network ◽  
Ghg Emissions ◽  
Three Dimensions ◽  
Mixed Integer ◽  
Particle Swarm Algorithm ◽  
Hub Location ◽  
Hub Location Problem ◽  
Health Crisis ◽  
Job Opportunities ◽  
The Social

By creating new job opportunities and developing the regional economy, the transport of goods generates significant costs, environmental and sanitary nuisances, and high greenhouse gas (GHG) emissions. In this context, collaboration is an interesting solution that can be used to enable companies to overcome some problems such as globalization, economic crisis, health crisis, issues related to sustainability, etc. This study deals with the design of a multiperiod multiproduct three-echelon collaborative distribution network with a heterogeneous fleet. By applying the mixed integer linear problem (MILP) formulations, it was possible to study the three dimensions of sustainability (economic, environmental, and social/societal). Since the examined problem was NP-hard, it was solved using four metaheuristic approaches to minimize the different logistics costs or CO2 emissions. The social/societal aspect evaluated the accident rate and the noise level generated by the freight transport. Four algorithms were developed to achieve our objectives: a genetic algorithm, a simulated annealing, a particle swarm algorithm, and a vibration damping optimization algorithm. Considering a French distribution network, these algorithms overcame the limits of the exact solution method by obtaining optimal solutions with reasonable execution time.

Impacts of Model Resolution on Transportation Network Criticality Rankings

2017 ◽  
Vol 2653 (1) ◽  
pp. 93-100 ◽  
Author(s):  
Jonathan Dowds ◽  
Karen Sentoff ◽  
James L. Sullivan ◽  
Lisa Aultman-Hall
Keyword(s):  
Travel Demand ◽  
Transportation Network ◽  
Network Connectivity ◽  
Network Robustness ◽  
Demand Models ◽  
Lower Volume ◽  
Travel Delay ◽  
The Impact ◽  
Aggregate Nature ◽  
Demand Aggregation

Objective rankings of the criticality of transportation network infrastructure are essential for efficiently allocating limited adaptation resources and must account for network connectivity and travel demand. Road link criticality can be quantified by the total travel delay caused when the capacity of a road segment or link is disrupted or removed. These methods can use standard travel demand models, but the exclusion of lower-volume roads and the aggregate nature of traffic analysis zones may distort resulting criticality rankings. To test the impact of link exclusion and demand aggregation, the authors applied the network robustness index, a well-established link criticality measure, to a hypothetical network with varying levels of network resolution and demand aggregation. The results show a statistically significant change in criticality rankings when demand is aggregated and especially when links are excluded from the network, suggesting that criticality rankings may be distorted when estimated with typical demand models. Application to a road network in Vermont supports the finding on the impact of network resolution on criticality rankings.

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.

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.

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