Petri net-based QUBO Model Formulation for Multi-Resource Flow-Shop Scheduling Problems

This paper introduces a Petri net-based approach to addressing multi-resource flow-shop scheduling problems within multi-objective quantum optimization. The multi-resource flow-shop problem, which holds both theoretical and practical significance, represents a real-world application scenario. The pr...

Full description

Saved in:
Bibliographic Details
Published in:International Symposium on Computing and Networking Workshops (Online) pp. 409 - 411
Main Authors: Uechi, Ryota, Nakamura, Morikazu, Shiroma, Tadashi, Nakachi, Takayuki
Format: Conference Proceeding
Language:English
Published: IEEE 26.11.2024
Subjects:
ISSN:2832-1324
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract This paper introduces a Petri net-based approach to addressing multi-resource flow-shop scheduling problems within multi-objective quantum optimization. The multi-resource flow-shop problem, which holds both theoretical and practical significance, represents a real-world application scenario. The practical nature of the problem necessitates incorporating multiple objective functions, which adds complexity to its formulation, particularly in representing the energy function within the QUBO (Quadratic Unconstrained Binary Optimization) model. Our approach mitigates the complexity of formulating the QUBO model by employing Petri net theory, providing a more efficient solution for these inherently complex problems. The paper further demonstrates the effectiveness of this method through computational examples utilizing a CPU-based QUBO optimization platform.
AbstractList This paper introduces a Petri net-based approach to addressing multi-resource flow-shop scheduling problems within multi-objective quantum optimization. The multi-resource flow-shop problem, which holds both theoretical and practical significance, represents a real-world application scenario. The practical nature of the problem necessitates incorporating multiple objective functions, which adds complexity to its formulation, particularly in representing the energy function within the QUBO (Quadratic Unconstrained Binary Optimization) model. Our approach mitigates the complexity of formulating the QUBO model by employing Petri net theory, providing a more efficient solution for these inherently complex problems. The paper further demonstrates the effectiveness of this method through computational examples utilizing a CPU-based QUBO optimization platform.
Author Nakachi, Takayuki
Uechi, Ryota
Nakamura, Morikazu
Shiroma, Tadashi
Author_xml – sequence: 1
  givenname: Ryota
  surname: Uechi
  fullname: Uechi, Ryota
  email: e215752@ie.u-ryukyu.ac.jp
  organization: University of the Ryukyus,Computer Sciences and Intelligent Systems, Faculty of Eng.,Okinawa,Japan
– sequence: 2
  givenname: Morikazu
  surname: Nakamura
  fullname: Nakamura, Morikazu
  email: morikazu@ie.u-ryukyu.ac.jp
  organization: University of the Ryukyus,Computer Sciences and Intelligent Systems, Faculty of Eng.,Okinawa,Japan
– sequence: 3
  givenname: Tadashi
  surname: Shiroma
  fullname: Shiroma, Tadashi
  email: shiroma@ie.u-ryukyu.ac.jp
  organization: University of the Ryukyus,Computer Sciences and Intelligent Systems, Faculty of Eng.,Okinawa,Japan
– sequence: 4
  givenname: Takayuki
  surname: Nakachi
  fullname: Nakachi, Takayuki
  email: takayuki.nakachi@ieee.org
  organization: University of the Ryukyus,Information Technology Center,Okinawa,Japan
BookMark eNotj8tOwkAYhUejiYi8gYnzAq1zvywRRU1AECQsydD-I2NKh0zbGN_eJro5Z_PlfDnX6KKONSB0R0lOKbH3k_Hb43i1VUJqljPCRE4IMeQMjay2hnMqieTCnqMBM5xllDNxhUZN89VjnBFBlBig7RLaFHANbbZ3DZT4ffOwwPNYQoWnMR27yrUh1tjHhOdd1YZsBU3sUgF4WsXvbH2IJ7wuDlB2Vag_8TLFfQXH5gZdelc1MPrvIdpMnz4mL9ls8fw6Gc-yQLXqnUS60lMFEkojHEhHgRGQpWeaWl0w7o13qtDM2_4L8EIbtdeqT8FJIfgQ3f7tBgDYnVI4uvSzo8RQbSznv0viVVA
CODEN IEEPAD
ContentType Conference Proceeding
DBID 6IE
6IL
CBEJK
RIE
RIL
DOI 10.1109/CANDARW64572.2024.00080
DatabaseName IEEE Electronic Library (IEL) Conference Proceedings
IEEE Xplore POP ALL
IEEE Xplore All Conference Proceedings
IEEE Electronic Library (IEL)
IEEE Proceedings Order Plans (POP All) 1998-Present
DatabaseTitleList
Database_xml – sequence: 1
  dbid: RIE
  name: IEEE Electronic Library (IEL)
  url: https://ieeexplore.ieee.org/
  sourceTypes: Publisher
DeliveryMethod fulltext_linktorsrc
EISBN 9798331505349
EISSN 2832-1324
EndPage 411
ExternalDocumentID 10817893
Genre orig-research
GroupedDBID 6IE
6IF
6IL
6IN
AAWTH
ABLEC
ADZIZ
ALMA_UNASSIGNED_HOLDINGS
BEFXN
BFFAM
BGNUA
BKEBE
BPEOZ
CBEJK
CHZPO
IEGSK
OCL
RIE
RIL
ID FETCH-LOGICAL-i176t-b05adf16e5ed84ae5a1e20e5df27197c23f8fa6c72f9349e3c786b76786430c43
IEDL.DBID RIE
ISICitedReferencesCount 0
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001440518400072&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
IngestDate Wed Jan 08 06:10:43 EST 2025
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-i176t-b05adf16e5ed84ae5a1e20e5df27197c23f8fa6c72f9349e3c786b76786430c43
PageCount 3
ParticipantIDs ieee_primary_10817893
PublicationCentury 2000
PublicationDate 2024-Nov.-26
PublicationDateYYYYMMDD 2024-11-26
PublicationDate_xml – month: 11
  year: 2024
  text: 2024-Nov.-26
  day: 26
PublicationDecade 2020
PublicationTitle International Symposium on Computing and Networking Workshops (Online)
PublicationTitleAbbrev CANDARW
PublicationYear 2024
Publisher IEEE
Publisher_xml – name: IEEE
SSID ssj0003204064
Score 1.8903158
Snippet This paper introduces a Petri net-based approach to addressing multi-resource flow-shop scheduling problems within multi-objective quantum optimization. The...
SourceID ieee
SourceType Publisher
StartPage 409
SubjectTerms Complexity theory
Computational efficiency
Computational modeling
Conferences
Job shop scheduling
Linear programming
multi-resource flow shop scheduling
Optimization
Optimization models
petri net
Petri nets
Processor scheduling
qubo model
Title Petri net-based QUBO Model Formulation for Multi-Resource Flow-Shop Scheduling Problems
URI https://ieeexplore.ieee.org/document/10817893
WOSCitedRecordID wos001440518400072&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1NTwIxEG2EePCkRoyKmh68Vrf70dkeEd14QhQJ3Eg_lYTsEj7079uWBb148Nb00mba5r1M581D6EYrqxXVgvA8sySlIiOSU0kklRoUFRDxjdkE9Hr5eMz7tVg9aGGMMaH4zNz6YfjL15Va-1SZe-E5BQewDdQAYBux1i6hksTuPrK0ruGiEb_rdnoPndcRSzPwkqvY98kO_R9_-agEGCkO_7mBI9T6EeTh_g5qjtGeKU_QKLhh4dKsiMcijV-G98_Ym5vNcOGoaG3MhR0txUFnS7a5elzMqi8y-KjmeOAOTftq9He_gPeWWbbQsHh86z6R2ieBTCkwt0aUCW0pM5nReSpMJqiJI5NpGwPloOLE5lYwBbHlScpNoiBnEhxMOToSqTQ5Rc2yKs0ZwgKEUsBVbpUjJlLyVDgKI5VjAi6kmp-jlo_KZL5phTHZBuTij_k2OvCB9-K9mF2i5mqxNldoX32upsvFdTjAb8PnnP8
linkProvider IEEE
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV09T8MwELWgIMEEiCK-8cBqiB0njsdSiIooodBW7Vb5EypVTdUP-PvYaVpYGNgsL47uHL2n8717AFxrZbXCWiCeRBZRLCIkOZZIYqmZwoIFfGk2wbIs6fd5qxSrF1oYY0zRfGZu_LJ4y9e5WvhSmfvDE8wcwG6CrYhSEizlWuuSSkjcjYxp2cWFA35br2X3tbdeTCPmRVfET8ouJkD-clIpgCTd--cn7IPqjyQPttZgcwA2zPgQ9Ao_LDg2c-TRSMPX7t0L9PZmI5g6Mlpac0FHTGGhtEWraj1MR_kXan_kE9h2adO-H_3dH-DdZWZV0E0fOvUGKp0S0BCz2J0RREJbHJvI6IQKEwlsSGAibQnDnCkS2sSKWDFieUi5CRVLYskcUDlCEigaHoHKOB-bYwAFE0oxrhKrHDWRklPhSIxUjgu4kGp-Aqo-KoPJchjGYBWQ0z_2r8BOo_PcHDQfs6czsOuT4KV8JD4Hlfl0YS7AtvqcD2fTyyKZ3x9XoEY
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=International+Symposium+on+Computing+and+Networking+Workshops+%28Online%29&rft.atitle=Petri+net-based+QUBO+Model+Formulation+for+Multi-Resource+Flow-Shop+Scheduling+Problems&rft.au=Uechi%2C+Ryota&rft.au=Nakamura%2C+Morikazu&rft.au=Shiroma%2C+Tadashi&rft.au=Nakachi%2C+Takayuki&rft.date=2024-11-26&rft.pub=IEEE&rft.eissn=2832-1324&rft.spage=409&rft.epage=411&rft_id=info:doi/10.1109%2FCANDARW64572.2024.00080&rft.externalDocID=10817893