An efficient algorithm for minimizing earliness, tardiness, and due-date costs for equal-sized jobs

Chung Lun Li; Gur Mosheiov; Uri Yovel

doi:10.1016/j.cor.2007.03.006

An efficient algorithm for minimizing earliness, tardiness, and due-date costs for equal-sized jobs

Chung Lun Li^*, Gur Mosheiov, Uri Yovel

^*Corresponding author for this work

Business Administration

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

We consider a single-machine scheduling problem with equal-sized jobs. The objective is to minimize the maximum weighted earliness-tardiness and due-date costs. We present an algorithm to solve this problem. Our algorithm makes use of bottleneck jobs and priority queues, and has a computational complexity of O (n⁴ log n). This complexity is a significant improvement of the existing algorithm in the literature.

Original language	English
Pages (from-to)	3612-3619
Number of pages	8
Journal	Computers and Operations Research
Volume	35
Issue number	11
DOIs	https://doi.org/10.1016/j.cor.2007.03.006
State	Published - Nov 2008

Bibliographical note

Funding Information:
The authors would like to thank two anonymous referees for their helpful comments and suggestions. This research was supported in part by the Recanati Fund of The School of Business Administration, The Hebrew University, Jerusalem, Israel and by Grant PolyU 5222/06E from the Hong Kong Research Grants Council.

Keywords

Analysis of algorithms
Due-date assignment
Earliness-tardiness
Scheduling

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10.1016/j.cor.2007.03.006

Cite this

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abstract = "We consider a single-machine scheduling problem with equal-sized jobs. The objective is to minimize the maximum weighted earliness-tardiness and due-date costs. We present an algorithm to solve this problem. Our algorithm makes use of bottleneck jobs and priority queues, and has a computational complexity of O (n4 log n). This complexity is a significant improvement of the existing algorithm in the literature.",

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AB - We consider a single-machine scheduling problem with equal-sized jobs. The objective is to minimize the maximum weighted earliness-tardiness and due-date costs. We present an algorithm to solve this problem. Our algorithm makes use of bottleneck jobs and priority queues, and has a computational complexity of O (n4 log n). This complexity is a significant improvement of the existing algorithm in the literature.

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An efficient algorithm for minimizing earliness, tardiness, and due-date costs for equal-sized jobs

Abstract

Bibliographical note

Keywords

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