Single-Machine Scheduling with Job-Position-Dependent Learning and Time-Dependent Deterioration

Document Type

Article

Publication Date

1-1-2012

Abstract

Job deterioration and learning co-exist in many realistic scheduling situations. This paper introduces a general scheduling model that considers the effects of position-dependent learning and time-dependent deterioration simultaneously. In the proposed model, the actual processing time of a job depends not only on the total processing time of the jobs already processed but also on its scheduled position. This paper focuses on the singlemachine scheduling problems with the objectives of minimizing the makespan, total completion time, total weighted completion time, discounted total weighted completion time, and maximum lateness based on the proposed model, respectively. It shows that they are polynomially solvable and optimal under certain conditions. Additionally, it presents some approximation algorithms based on the optimal schedules for the corresponding single-machine scheduling problems and analyzes their worst case error bound. © 2012, IEEE

Identifier

84655167721 (Scopus)

Publication Title

IEEE Transactions on Systems Man and Cybernetics Part A Systems and Humans

External Full Text Location

https://doi.org/10.1109/TSMCA.2011.2147305

e-ISSN

15582426

ISSN

10834427

First Page

192

Last Page

200

Issue

1

Volume

42

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