A simultaneous bus route network design and frequency setting model is formulated as the weighted sum multiobjective genetic algorithm optimization. It aims to search for a near-optimum set of routes and corresponding frequencies while minimizing both user and operator costs. It is a nondeterministic polynomial time complete optimization problem, and searching the entire space through metaheuristic algorithms is impractical. It does require narrowing down the search space into some feasible regions. In this paper, two strategies are implemented, offering a distinct advantage in the finding of near-optimum solutions. First, a set of constraints are imposed on resources defined through experience and route generation and filtration algorithms are implemented to increase the quality of the candidate solution pool. Second, in order to increase the probability of selecting better performing set of routes and reducing genetic algorithm’s degree of randomness, a specially designed transfer minimization operator is implemented within the optimization procedure. Results are then compared on the basis of Mandl’s network that has been used as the benchmark by various researchers. Further, the sensitivity of the model to different rules and parameters is carried out. Obtained solutions perform better as compared to the previous techniques.
Simultaneous Bus Transit Route Network and Frequency Setting Search Algorithm
2019-02-15
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Urban Transit Route Network Design Problem using Tabu Search Algorithm
British Library Conference Proceedings | 2007
|Transit Route Network Design Using Frequency Coded Genetic Algorithm
Online Contents | 2003
|Transit Route Network Design Using Frequency Coded Genetic Algorithm
British Library Online Contents | 2003
|Integrating Frequency Setting, Timetabling, and Route Assignment to Synchronize Transit Lines
DOAJ | 2019
|