Transit Network Design: The Necessity of Elastic Demand Consideration

2011 ◽  
Vol 97-98 ◽  
pp. 1117-1122 ◽  
Author(s):  
Andisheh Ranjbari ◽  
Afshin Shariat Mohaymany ◽  
S. M. Mahdi Amiripour

Transit network design as the first and critical phase of public transportation planning is extremely sensitive to transit demand. An important characteristic of transit demand is elasticity or service-dependency, which means that any change in the service offered by the system is followed by a change in transit demand. Due to the complexity of transit network design problem (TNDP) researchers have usually assumed transit demand to be fixed rather than elastic; while ignoring this issue may result in inefficiency of system, dissatisfaction of users, and system failure, since the predicted amount of passengers would not use the transit system. This paper aims to demonstrate the necessity of elastic demand consideration in transit network design, and proposes a solution framework, which is composed of a preparation stage and an iterative procedure. A case study example is presented subsequently, to show the use of this solution method and further illustrates the necessity of considering this issue. Three cases of truly predicted demand (considering elastic demand), overestimated and underestimated demands (in the absence of elastic demand consideration) are defined, and the performance measures of these cases are compared to those in the base mode. The results show that elastic demand consideration leads to the optimal network, in which the system efficiently matches between supply and demand.

Author(s):  
Avishai Ceder ◽  
Yechezkel Israeli

The basic construction of the objective functions of the transit network design problem is described, and a new approach taking account of both passenger and operator interests is proposed. The approach presented combines the philosophy of the mathematical programming approaches with decision-making techniques in order to allow the user to select from a number of alternatives. The nature of the overall formulation is nonlinear and mixed-integer programming.


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