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2018 | Supplement | Chapter

Fuzzy Bi-objective Chance-Constrained Programming Model for Timetable Optimization of a Bus Route

Authors : Hejia Du, Hongguang Ma, Xiang Li

Published in: Advances in Computational Intelligence Systems

Publisher: Springer International Publishing

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Abstract

Timetable optimization is essential to the improvement of a bus operating company’s economic profits, quality of service and competitiveness in the market. The most previous researches studied the bus timetabling with assuming the passenger demand is certain but it varies in practice. In this study, we consider a timetable optimization problem of a single bus line under fuzzy environment. Assuming the passenger quantity in per time segment is a fuzzy value, a fuzzy bi-objective programming model that maximizes the total passenger volume and minimizes the total bus travel time under a capacity rate constraint is established. This chance constrained programming model is formulated with the passenger volume and capacity rate under certain chance constraints. Furthermore, a genetic algorithm of variable length is designed to solve the proposed model. Finally, we present a case study that utilizing real data obtained from a major Beijing bus operating company to illustrate the proposed model and algorithm.

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Title: Fuzzy Bi-objective Chance-Constrained Programming Model for Timetable Optimization of a Bus Route
Authors: Hejia Du
Hongguang Ma
Xiang Li
Publisher: Springer International Publishing
Book: Advances in Computational Intelligence Systems
Print ISBN: 978-3-319-66938-0

Electronic ISBN: 978-3-319-66939-7

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-66939-7_27

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