PARALLEL-MACHINE SCHEDULING IN SHARED MANUFACTURING

Min Ji; Xinna Ye; Fangyao Qian; T. C.E. Cheng; Yiwei Jiang

doi:10.3934/jimo.2020174

PARALLEL-MACHINE SCHEDULING IN SHARED MANUFACTURING

Min Ji
, Xinna Ye
, Fangyao Qian
, T. C.E. Cheng
, Yiwei Jiang

Research output: Journal article publication › Journal article › Academic research › peer-review

17 Citations (Scopus)

Abstract

We consider parallel-machine scheduling in the context of shared manufacturing where each job has a machine set to which it can be assigned for processing. Such a set is called the processing set. In the shared manufacturing setting, a job can be assigned not only to certain machines for processing, but can also be processed on the remaining machines at a certain cost. Compared with traditional scheduling with job rejection, the scheduling model under study embraces the notion of sustainable manufacturing. Showing that the problem is NP-hard, we develop a fully polynomial-time approximation scheme to solve the problem when the number of machines is fixed.

Original language	English
Pages (from-to)	881-891
Number of pages	11
Journal	Journal of Industrial and Management Optimization
Volume	18
Issue number	1
DOIs	https://doi.org/10.3934/jimo.2020174
Publication status	Published - Jan 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

FPTAS
parallel machines
processing set
Scheduling
shared manufacturing

ASJC Scopus subject areas

Business and International Management
Strategy and Management
Control and Optimization
Applied Mathematics

More information

10.3934/jimo.2020174

Cite this

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title = "PARALLEL-MACHINE SCHEDULING IN SHARED MANUFACTURING",

abstract = "We consider parallel-machine scheduling in the context of shared manufacturing where each job has a machine set to which it can be assigned for processing. Such a set is called the processing set. In the shared manufacturing setting, a job can be assigned not only to certain machines for processing, but can also be processed on the remaining machines at a certain cost. Compared with traditional scheduling with job rejection, the scheduling model under study embraces the notion of sustainable manufacturing. Showing that the problem is NP-hard, we develop a fully polynomial-time approximation scheme to solve the problem when the number of machines is fixed.",

keywords = "FPTAS, parallel machines, processing set, Scheduling, shared manufacturing",

author = "Min Ji and Xinna Ye and Fangyao Qian and Cheng, \{T. C.E.\} and Yiwei Jiang",

note = "Funding Information: This research was supported in part by the National Natural Science Foundation of China under grant numbers 11971434 and 11871327, Zhejiang Provincial Natural Science Foundation of China under grant number LY21G010002, and the Contemporary Business and Trade Research Center of Zhejiang Gongshang University, which is a key Research Institute of Social Sciences and Humanities of the Ministry of Education of China. Cheng was supported in part by The Hong Kong Polytechnic University under the Fung Yiu King - Wing Hang Bank Endowed Professorship in Business Administration. ∗ Corresponding author: Yiwei Jiang. Publisher Copyright: {\textcopyright} 2022. All Rights Reserved.",

year = "2022",

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doi = "10.3934/jimo.2020174",

language = "English",

volume = "18",

pages = "881--891",

journal = "Journal of Industrial and Management Optimization",

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AU - Ji, Min

AU - Ye, Xinna

AU - Qian, Fangyao

AU - Cheng, T. C.E.

AU - Jiang, Yiwei

N1 - Funding Information: This research was supported in part by the National Natural Science Foundation of China under grant numbers 11971434 and 11871327, Zhejiang Provincial Natural Science Foundation of China under grant number LY21G010002, and the Contemporary Business and Trade Research Center of Zhejiang Gongshang University, which is a key Research Institute of Social Sciences and Humanities of the Ministry of Education of China. Cheng was supported in part by The Hong Kong Polytechnic University under the Fung Yiu King - Wing Hang Bank Endowed Professorship in Business Administration. ∗ Corresponding author: Yiwei Jiang. Publisher Copyright: © 2022. All Rights Reserved.

PY - 2022/1

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N2 - We consider parallel-machine scheduling in the context of shared manufacturing where each job has a machine set to which it can be assigned for processing. Such a set is called the processing set. In the shared manufacturing setting, a job can be assigned not only to certain machines for processing, but can also be processed on the remaining machines at a certain cost. Compared with traditional scheduling with job rejection, the scheduling model under study embraces the notion of sustainable manufacturing. Showing that the problem is NP-hard, we develop a fully polynomial-time approximation scheme to solve the problem when the number of machines is fixed.

AB - We consider parallel-machine scheduling in the context of shared manufacturing where each job has a machine set to which it can be assigned for processing. Such a set is called the processing set. In the shared manufacturing setting, a job can be assigned not only to certain machines for processing, but can also be processed on the remaining machines at a certain cost. Compared with traditional scheduling with job rejection, the scheduling model under study embraces the notion of sustainable manufacturing. Showing that the problem is NP-hard, we develop a fully polynomial-time approximation scheme to solve the problem when the number of machines is fixed.

KW - FPTAS

KW - parallel machines

KW - processing set

KW - Scheduling

KW - shared manufacturing

UR - https://www.scopus.com/pages/publications/85123256512

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DO - 10.3934/jimo.2020174

M3 - Journal article

AN - SCOPUS:85123256512

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VL - 18

SP - 881

EP - 891

JO - Journal of Industrial and Management Optimization

JF - Journal of Industrial and Management Optimization

IS - 1

ER -

PARALLEL-MACHINE SCHEDULING IN SHARED MANUFACTURING

Abstract

UN SDGs

Keywords

ASJC Scopus subject areas

More information

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