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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Vydáno v:	Annals of operations research Ročník 296; číslo 1-2; s. 131 - 162
Hlavní autoři:	Kaveh, Firoozeh, Tavakkoli-Moghaddam, Reza, Triki, Chefi, Rahimi, Yaser, Jamili, Amin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.01.2021 Springer Springer Nature B.V
Témata:	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
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Abstract	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.
AbstractList	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.
Audience	Academic
Author	Tavakkoli-Moghaddam, Reza Kaveh, Firoozeh Jamili, Amin Triki, Chefi Rahimi, Yaser
Author_xml	– sequence: 1 givenname: Firoozeh surname: Kaveh fullname: Kaveh, Firoozeh organization: School of Industrial Engineering, College of Engineering, University of Tehran – sequence: 2 givenname: Reza surname: Tavakkoli-Moghaddam fullname: Tavakkoli-Moghaddam, Reza organization: School of Industrial Engineering, College of Engineering, University of Tehran, Arts et Métiers ParisTech, LCFC – sequence: 3 givenname: Chefi surname: Triki fullname: Triki, Chefi email: ctriki@hbku.edu.qa organization: College of Science and Engineering, Hamad Bin Khalifa University, Department of Engineering for Innovation, University of Salento – sequence: 4 givenname: Yaser surname: Rahimi fullname: Rahimi, Yaser organization: School of Industrial Engineering, College of Engineering, University of Tehran – sequence: 5 givenname: Amin surname: Jamili fullname: Jamili, Amin organization: School of Industrial Engineering, College of Engineering, University of Tehran
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SubjectTerms	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
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Title	A new bi-objective model of the urban public transportation hub network design under uncertainty
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