A multi-objective robust possibilistic programming approach to sustainable public transportation network design

2020 ◽  
Author(s):  
Elif Elçin Günay ◽  
Gül E. Okudan Kremer ◽  
Atousa Zarindast
Keyword(s):  
Network Design ◽  
Public Transportation ◽  
Transportation Network ◽  
Programming Approach ◽  
Multi Objective ◽  
Possibilistic Programming ◽  
Public Transportation Network

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

2019 ◽  
Vol 296 (1-2) ◽  
pp. 131-162 ◽  
Author(s):  
Firoozeh Kaveh ◽  
Reza Tavakkoli-Moghaddam ◽  
Chefi Triki ◽  
Yaser Rahimi ◽  
Amin Jamili
Keyword(s):  
Public Transportation ◽  
Transportation Network ◽  
Hub Location ◽  
Construction Costs ◽  
Hub Location Problem ◽  
Multi Objective ◽  
Multi Objective Programming ◽  
Objective Model ◽  
Hub Network ◽  
Public Transportation Network

AbstractThis 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.

scholarly journals Performance Comparison between the Multi-Colony and Multi-Pheromone ACO Algorithms for Solving the Multi-objective Routing Problem in a Public Transportation Network

2015 ◽  
Vol 69 (1) ◽  
pp. 197-210 ◽  
Author(s):  
Hamed Faroqi ◽  
Mohammad saadi Mesgari
Keyword(s):  
Public Transportation ◽  
Transportation Network ◽  
Performance Comparison ◽  
Objective Functions ◽  
Routing Problem ◽  
The Public ◽  
Multi Objective ◽  
Large Size ◽  
Public Transportation Network ◽  
Complicated Task

Routing in a multimodal urban public transportation network, according to the user's preferences, can be considered as a multi-objective optimisation problem. Solving this problem is a complicated task due to the different and incompatible objective functions, various modes in the network, and the large size of the network. In this research, two optimisation algorithms are considered for solving this problem. The multi-colony and multi-pheromone Ant Colony Optimisation (ACO) algorithms are two different modes of the Multi-Objective ACO (MOACO) algorithm. Moreover, according to the acquired information, the algorithms implemented in the public transportation network of Tehran consist of four modes. In addition, three objective functions have been simultaneously considered as the problem's objectives. The algorithms are run with different initial parameters and afterwards, the results are compared and evaluated based on the different obtained routes and with the aid of the convergence and repeatability tests, diversity and convergence metrics.

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