An ε-Constraint Multi-objective Algorithm for Transit Route Design with Subsidy Consideration

Abstract

Smart City has been proposed to be a total solution for cities around the world. Public transportation, as one of the basic element in a Smart City, provides shared transport service, such as bus, light rail transit (LRT), and mass rapid transit (MRT), to save energy, reduce air pollution and relieve congestion. For transit operators, how to provide efficient and effective service in traffic networks with limited budget is an important issue. As more public transportation is deployed under the same budget, how to balance bus route and subsidy becomes a new issue. The research proposes a multi-objective formulation to design the optimal bus routes under three conflicting objectives, including travel cost, demand, and subsidy. The solution algorithm is constructed based on the ε-constraint method to solve the problem. Numerical experiments based on a realistic network in Chiayi (Taiwan) are conducted to illustrate the proposed algorithm.