Parallel Machine Scheduling Considering the Moving Time of Multiple Servers (다중 서버의 이동 시간을 고려하는 병렬 머신 스케줄링)

Kyun Rak Chong (정균락)

doi:10.9708/jksci.2017.22.10.101

Parallel Machine Scheduling Considering the Moving Time of Multiple Servers

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2017, 22(10), pp.101-107
DOI : 10.9708/jksci.2017.22.10.101
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : August 1, 2017
Accepted : October 11, 2017
Published : October 31, 2017

Kyun Rak Chong ¹

¹홍익대학교

Accredited

ABSTRACT

In this paper, we study the problem of parallel machine scheduling considering the moving time of multiple servers. The parallel machine scheduling is to assign jobs to parallel machines so that the total completion time(makespan) is minimized. Each job has a setup phase, a processing phase and a removal phase. A processing phase is performed by a parallel machine alone while a setup phase and a removal phase are performed by both a server and a parallel machine simultaneously. A server is needed to move to a parallel machine for a setup phase and a removal phase. But previous researches have been done under the assumption that the server moving time is zero. In this study we have proposed an efficient algorithm for the problem of parallel machine scheduling considering multiple server moving time. We also have investigated experimentally how the number of servers and the server moving time affect the total completion time.

KEYWORDS

parallel machine scheduling, total completion time, multiple server, server moving time

Citation status

* References for papers published after 2023 are currently being built.

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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Parallel Machine Scheduling Considering the Moving Time of Multiple Servers

ABSTRACT

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Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Parallel Machine Scheduling Considering the Moving Time of Multiple Servers

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.