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Amirali Zarrinmehr

Amirali Zarrinmehr

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Faculty of Technology and Engineering
Address: Uiversity of Mazandaran
Phone: 011-35302903

Research

Title
A hill climbing approach to find optimal public transit routes configuration
Type
Presentation
Keywords
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Year
2020
Researchers Amirali Zarrinmehr

Abstract

Regarding the experience of urban planning and development in recent decades, it has been widely recognized that the shift towards private transportation in daily commuting may lead to many challenging issues such as air pollution and traffic congestion. As a result, an effective public transportation system (i.e. transit system) has been a recurrent theme in transportation research to achieve a viable option in moving towards sustainable transportation. Establishing a network of transit routes with satisfactory share of transit commuters has been one of the main goals of transit agencies in moving towards a sustainable urban development. In general, the problem of Transit Routes Network Design aims at selecting the most efficient configuration of public transit routes in an urban area. In this study, a new approach is adopted based on selecting optimal “sub-routes”. The study assumes that a set of pre-defined candidate routes are available from a previous analysis of the network. For each candidate route, a sub-route (rather than the entire route) may be taken into account for construction. It is intended to maximize the transit share of the demand (modeled through a logit model), while also taking into account users’ response to various design alternatives. Such a problem is formulated in a bi-level framework, in which the Lower Level Problem is an auto-transit traffic assignment problem, and the Upper Level Problem involves finding the sub-routes configuration. In the lower level problem, to incorporate users’ behavior of choosing between public and private modes of transportation, a path-based assignment tool (based on a complementarity assignment formulation) is implemented and applied. This assignment tool is shown to lend itself well to the proposed algorithm of the upper level in this study. Two efficient heuristic solution algorithms in recent literature, namely a “hill climbing” algorithm and a “greedy” algorithm, are taken into account. The structure of b