A multi-objective meta-heuristic approach for transit network design and frequency setting problem in a bus transit system

Abstract

This paper studies a multi-objective transit network design and frequency setting (TNDFS) problem with the aim of determining a set of routes and frequency on each route for public buses. The TNDFS problem is solved in two stages. First, the transit network design problem is solved to generate a set of routes using an initial route set generation (IRSG) procedure combined with genetic algorithm. Second, the frequency setting problem is formulated as a multi-objective model to assign the frequency on each route with the objectives of minimizing the passenger time and the operating cost simultaneously. This problem is solved using the multi-objective particle swarm optimization with multiple search strategies (MMOPSO) to generate a Pareto-Front between the passenger time and the operating cost. An extensive computational experiment is performed on the benchmark Mandl’s Swiss network (Mandl, 1980) considering different scenarios and instances. The results obtained using the proposed approach to solve the transit network design problem are compared with that of the state-of-the-art methodologies available in the literature (Arbex & Cunha, 2015; Kechagiopoulos & Beligiannis, 2014; Nikolić & Teodorović, 2013), which outperforms in terms of trip directness and average travel time of passengers. For the frequency setting problem, the solutions obtained using MMOPSO are justified over the NSGA-II.