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. (C) 2018 Elsevier Ltd. All rights reserved.
展开▼
