A new bi-objective model of the urban public transportation hub network design under uncertainty

This paper presents a new bi-objective multi-modal hub location problem with multiple assignment and capacity considerations for the design of an urban public transportation network under uncertainty. Because of the high construction costs of hub links in an urban public transportation network, it i...

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Bibliographic Details
Published in:Annals of operations research Vol. 296; no. 1-2; pp. 131 - 162
Main Authors: Kaveh, Firoozeh, Tavakkoli-Moghaddam, Reza, Triki, Chefi, Rahimi, Yaser, Jamili, Amin
Format: Journal Article
Language:English
Published: New York Springer US 01.01.2021
Springer
Springer Nature B.V
Subjects:
Business and Management
Combinatorics
Construction costs
Genetic algorithms
Heuristic methods
Mathematical programming
Monorails
Multiple objective analysis
Network design
Operations research
Operations Research/Decision Theory
Particle swarm optimization
Public transportation
S.i.: Mopgp 2017
Site selection
Sorting algorithms
Theory of Computation
Uncertainty
Urban transportation
Iran
Elastic demand
Urban transportation
Capacitated hub location problem
Fuzzy multi-objective programming
Meta-heuristics
ISSN:0254-5330, 1572-9338
Online Access:Get full text
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Summary:This paper presents a new bi-objective multi-modal hub location problem with multiple assignment and capacity considerations for the design of an urban public transportation network under uncertainty. Because of the high construction costs of hub links in an urban public transportation network, it is not economic to create a complete hub network. Moreover, the demand is assumed to be dependent on the utility proposed by each hub. Thus, the elasticity of the demand is considered in this paper. The presented model also has the ability to compute the number of each type of transportation vehicles between every two hubs. The objectives of this model are to maximize the benefits of transportation by establishing hub facilities and to minimize the total transportation time. Since exact values of some parameters are not known in advance, a fuzzy multi-objective programming based approach is proposed to optimally solve small-sized problems. For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. Our experimental results demonstrated the validity of our developed model and approaches. Moreover, an intensive sensitivity analyze study is carried out on a real-case application related to the monorail project of the holy city of Qom.
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-019-03430-9