An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem
Joint Authors
Mou, Jianhui
Li, Xinyu
Gao, Liang
Lu, Chao
Zhang, Guohui
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-23
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
The goal of the scheduling is to arrange operations on suitable machines with optimal sequence for corresponding objectives.
In order to meet market requirements, scheduling systems must own enough flexibility against uncertain events.
These events can change production status or processing parameters, even causing the original schedule to no longer be optimal or even to be infeasible.
Traditional scheduling strategies, however, cannot cope with these cases.
Therefore, a new idea of scheduling called inverse scheduling has been proposed.
In this paper, the inverse scheduling with weighted completion time (SMISP) is considered in a single-machine shop environment.
In this paper, an improved genetic algorithm (IGA) with a local searching strategy is proposed.
To improve the performance of IGA, efficient encoding scheme, fitness evaluation mechanism, feasible initialization methods, and a local search procedure have been employed in the paper.
Because of the local improving method, the proposed IGA can balance its exploration ability and exploitation ability.
We adopt 27 instances to verify the effectiveness of the proposed algorithm.
The experimental results illustrated that the proposed algorithm can generate satisfactory solutions.
This approach also has been applied to solve the scheduling problem in the real Chinese shipyard and can bring some benefits.
American Psychological Association (APA)
Mou, Jianhui& Li, Xinyu& Gao, Liang& Lu, Chao& Zhang, Guohui. 2014. An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-466669
Modern Language Association (MLA)
Mou, Jianhui…[et al.]. An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem. Mathematical Problems in Engineering No. 2014 (2014), pp.1-14.
https://search.emarefa.net/detail/BIM-466669
American Medical Association (AMA)
Mou, Jianhui& Li, Xinyu& Gao, Liang& Lu, Chao& Zhang, Guohui. An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-466669
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-466669