A fuzzy simulated evolution algorithm for the driver scheduling problem

Author

Li, Jingpeng ; Kwan, Raymond S K

Author_Institution

Sch. of Comput., Leeds Univ., UK

Volume

2

fYear

2001

fDate

2001

Firstpage

1115

Abstract

The paper presents a fuzzy simulated evolution algorithm for the public transport driver scheduling problem, which involves solving a set covering model. The novel scheduling algorithm incorporates the idea of fuzzy evaluation into simulated evolution, combining the features of iterative improvement and constructive perturbation, to explore solution space effectively and obtain superior schedules. Experiments with benchmark tests using data from the transportation industry demonstrate the strengths of the proposed algorithm in solving large size real-world driver scheduling problems. It is suggested that this approach might be suitable for other large-scale set covering problems

Keywords

driver information systems; evolutionary computation; fuzzy set theory; scheduling; search problems; set theory; transportation; benchmark tests; constructive perturbation; driver scheduling problem; fuzzy evaluation; fuzzy simulated evolution algorithm; iterative improvement; large size real-world driver scheduling problems; large-scale set covering problems; public transport driver scheduling problem; scheduling algorithm; set covering model; solution space; transportation industry; Computational modeling; Costs; Fuses; Iterative algorithms; Job shop scheduling; Law; Legal factors; Processor scheduling; Scheduling algorithm; Space exploration;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2001. Proceedings of the 2001 Congress on

Conference_Location

Seoul

Print_ISBN

0-7803-6657-3

Type

conf

DOI

10.1109/CEC.2001.934316

Filename

934316