Complete hierarchical multi-objective genetic algorithm for transit network design problem

Abstract

Transit Network Design Problem is a multi-disciplinary problem that is considered one of the most intractable problems for real size networks. In the late 90s, Meta-heuristics started to prove more reliability to the problem. Genetic Algorithm (GA) is one of the popular Meta-heuristics which is usually implemented because it is simply adapted to the problem. In this study, GA is presented as a complete constructive multi-objective algorithm that creates its own routes from scratch then assembles the routes into efficient transit networks. Finally, it handles the multi-criteria nature of the problem until producing the optimal (near optimal) Pareto front solutions. A new frequency setting algorithm is also developed based on simulation results at the bus stop level which takes the bi-level decision making of both users and operators implicitly. Experimental studies on two real size networks are conducted to validate the methodology performance and robustness.