Maximizing total job value on a single machine with job selection

Joonyup Eun; Chang Sup Sung; Eun Seok Kim

doi:10.1057/s41274-017-0238-z

Maximizing total job value on a single machine with job selection

Joonyup Eun, Chang Sup Sung, Eun Seok Kim

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

1 Citation (Scopus)

Abstract

This paper describes a single-machine scheduling problem of maximizing total job value with a machine availability constraint. The value of each job decreases over time in a stepwise fashion. Several solution properties of the problem are developed. Based on the properties, a branch-And-bound algorithm and a heuristic algorithm are derived. These algorithms are evaluated in the computational study, and the results show that the heuristic algorithm provides effective solutions within short computation times.

Original language	English
Pages (from-to)	998-1005
Number of pages	8
Journal	Journal of the Operational Research Society
Volume	68
Issue number	9
DOIs	https://doi.org/10.1057/s41274-017-0238-z
Publication status	Published - 2017 Sep 1
Externally published	Yes

Keywords

branch-And-bound
heuristic
job value
scheduling
stepwise value function

ASJC Scopus subject areas

Modelling and Simulation
Strategy and Management
Statistics, Probability and Uncertainty
Management Science and Operations Research

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10.1057/s41274-017-0238-z

Cite this

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abstract = "This paper describes a single-machine scheduling problem of maximizing total job value with a machine availability constraint. The value of each job decreases over time in a stepwise fashion. Several solution properties of the problem are developed. Based on the properties, a branch-And-bound algorithm and a heuristic algorithm are derived. These algorithms are evaluated in the computational study, and the results show that the heuristic algorithm provides effective solutions within short computation times.",

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AB - This paper describes a single-machine scheduling problem of maximizing total job value with a machine availability constraint. The value of each job decreases over time in a stepwise fashion. Several solution properties of the problem are developed. Based on the properties, a branch-And-bound algorithm and a heuristic algorithm are derived. These algorithms are evaluated in the computational study, and the results show that the heuristic algorithm provides effective solutions within short computation times.

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Maximizing total job value on a single machine with job selection

Abstract

Keywords

ASJC Scopus subject areas

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