Joint Optimization of Temporal Headway and Differential Fare for Transit Systems Considering Heterogeneous Demand Elasticity

Abstract

This study presents an approach to jointly optimize temporal service headway and differential fare for an intercity transit system considering heterogeneous demand elasticity. The research optimization problem is combinatorial and difficult to solve analytically. A genetic algorithm is developed to search for the optimal solution, including temporal headway and differential fare, which maximizes the daily profit considering service capacity sufficiency and operable fleet size. A real world case study, the Taiwan High Speed Rail Line, is applied to demonstrate the applicability of the developed model and the efficiency of the solution algorithm to search for the optimal solution that yields the maximum profit operation. Results from the sensitivity analyses indicate that the optimized number of partitions of travel distance and headway decreases as the demand increases, which results in the increase of profit. The developed model can be applied to evaluate and plan an intercity rail system.