A novel mathematical model for the scheduling of a zero inventory production: an application of process scheduling in fog computing

•Considering a zero-inventory production-scheduling problem.•Presenting an MINLP model and linearizing it (turning it into a MILP model).•Designing an efficient GA to solve the problem and the developed MILP model.•Evaluating the model and GA with an IPS case on edge computing. One of the main produ...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Computers & operations research Ročník 185; s. 107284
Hlavní autori: Sharifi, Mani, Taghipour, Sharareh, Abhari, Abdolreza, Rysz, Maciej
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.01.2026
Predmet:
ISSN:0305-0548
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract •Considering a zero-inventory production-scheduling problem.•Presenting an MINLP model and linearizing it (turning it into a MILP model).•Designing an efficient GA to solve the problem and the developed MILP model.•Evaluating the model and GA with an IPS case on edge computing. One of the main production-related costs in manufacturing is inventory cost since manufacturing firms allocate a vast area to raw material, semi-processed, and final products in production lines and warehouses. Reducing the volume of these inventories leads to lower production-related costs. This paper presents a novel mathematical model for zero-inventory production scheduling. In this model, the jobs arrive at fixed times and are scheduled on a set of unrelated machines. The jobs have different operations that need to be processed one by one. Since the system has zero inventory, the jobs must be processed immediately upon arrival. Also, whenever a job’s operation is complete, the following operation must instantly start (no wait time). That operation is outsourced if no machines are available to process any of the job’s operations. The jobs’ operations are dispatched to the machines from a dispatching center, and there is a latency between the dispatching center, the machines, and the outsourcing center. We present a mixed-integer non-linear programming (MINLP) model to formulate this problem. Then, the MINLP model is turned into a mixed-integer linear programming (MILP) model by linearizing its constraints. Since many production scheduling problems are known to be NP-hard, particularly those involving unrelated parallel machines, precedence constraints, and time-dependent decisions like ours, we adopt two metaheuristics to solve the problem for large-scale cases where exact methods are computationally inefficient. The first is a Genetic Algorithm (GA), and the second is a Teaching-Learning-Based Optimization (TLBO) algorithm. The performance of these algorithms is tested against the optimal solutions obtained from CPLEX for a set of small-scale problems. We consider a real case study, an image processing system, to validate the proposed developments (the MILP model and the GA). The results show that the presented model and algorithm can reduce the system’s total cost by about 12.57% compared to the existing online dispatching rules.
AbstractList •Considering a zero-inventory production-scheduling problem.•Presenting an MINLP model and linearizing it (turning it into a MILP model).•Designing an efficient GA to solve the problem and the developed MILP model.•Evaluating the model and GA with an IPS case on edge computing. One of the main production-related costs in manufacturing is inventory cost since manufacturing firms allocate a vast area to raw material, semi-processed, and final products in production lines and warehouses. Reducing the volume of these inventories leads to lower production-related costs. This paper presents a novel mathematical model for zero-inventory production scheduling. In this model, the jobs arrive at fixed times and are scheduled on a set of unrelated machines. The jobs have different operations that need to be processed one by one. Since the system has zero inventory, the jobs must be processed immediately upon arrival. Also, whenever a job’s operation is complete, the following operation must instantly start (no wait time). That operation is outsourced if no machines are available to process any of the job’s operations. The jobs’ operations are dispatched to the machines from a dispatching center, and there is a latency between the dispatching center, the machines, and the outsourcing center. We present a mixed-integer non-linear programming (MINLP) model to formulate this problem. Then, the MINLP model is turned into a mixed-integer linear programming (MILP) model by linearizing its constraints. Since many production scheduling problems are known to be NP-hard, particularly those involving unrelated parallel machines, precedence constraints, and time-dependent decisions like ours, we adopt two metaheuristics to solve the problem for large-scale cases where exact methods are computationally inefficient. The first is a Genetic Algorithm (GA), and the second is a Teaching-Learning-Based Optimization (TLBO) algorithm. The performance of these algorithms is tested against the optimal solutions obtained from CPLEX for a set of small-scale problems. We consider a real case study, an image processing system, to validate the proposed developments (the MILP model and the GA). The results show that the presented model and algorithm can reduce the system’s total cost by about 12.57% compared to the existing online dispatching rules.
ArticleNumber 107284
Author Taghipour, Sharareh
Abhari, Abdolreza
Rysz, Maciej
Sharifi, Mani
Author_xml – sequence: 1
  givenname: Mani
  orcidid: 0000-0002-7682-7077
  surname: Sharifi
  fullname: Sharifi, Mani
  email: sharifm@miamioh.edu
  organization: Department of Information Systems & Analytics, Farmer School of Business, Miami University, Oxford, OH, USA
– sequence: 2
  givenname: Sharareh
  surname: Taghipour
  fullname: Taghipour, Sharareh
  organization: The Reliability, Risk, and Maintenance Research Laboratory (RRMR Lab), Department of Mechanical and Industrial Engineering, Toronto Metropolitan University, Toronto, Ontario, Canada
– sequence: 3
  givenname: Abdolreza
  surname: Abhari
  fullname: Abhari, Abdolreza
  organization: The Distributed Systems & Multimedia Processing Laboratory (DSMP Lab), Department of Computer Science, Toronto Metropolitan University, Toronto, Ontario, Canada
– sequence: 4
  givenname: Maciej
  orcidid: 0000-0003-2667-0398
  surname: Rysz
  fullname: Rysz, Maciej
  organization: Department of Information Systems & Analytics, Farmer School of Business, Miami University, Oxford, OH, USA
BookMark eNp9UE1vAiEU5GCTqu0P6I0_sBbWhV3bkzH9Skx6ac-EfTwUs8IGVhN77R8vxh56KgfIDDOT92ZCRj54JOSOsxlnXN7vZhDirGSlyLgum2pExmzORMFE1VyTSUo7lk9d8jH5XlIfjtjRvR62mC8HOoNgMmVDpJmkCbZoDp3zGxos1fQLY6DOH9EPIZ5oH4M5wOCCf6DaU933XQ4547M8_wKm9DfE-Ry9oRD2_WHIxA25srpLePv7Tsnn89PH6rVYv7-8rZbrAkrBh2IBshJmzivRWI6gG1kz0-Y9sG3sQhvdliW3UmIjwHKwC2mlMC0HmSXI6_mU8EsuxJBSRKv66PY6nhRn6tyc2qncnDo3py7NZc_jxYN5sKPDqBI49IDGRYRBmeD-cf8Aibp9vw
Cites_doi 10.1016/j.ijpe.2016.01.016
10.1016/j.cor.2021.105477
10.1016/j.asoc.2020.106208
10.1016/j.cor.2020.105031
10.1016/j.ins.2014.11.036
10.1016/j.cirpj.2021.03.006
10.1016/j.tcs.2021.05.022
10.1016/j.jmsy.2021.04.010
10.1109/RAMS48030.2020.9153629
10.1016/j.compind.2015.10.001
10.1016/j.cie.2020.106432
10.1109/TSMC.2017.2720178
10.1080/09537287.2019.1681534
10.1007/s10951-013-0342-0
10.1145/1735970.1736033
10.1109/TSMC.2012.2234943
10.4236/jcc.2016.44013
10.1177/0954405414564410
10.1016/j.asoc.2021.107312
10.1016/j.compchemeng.2020.107166
10.1016/j.jclepro.2017.10.342
10.1016/j.ejor.2019.09.033
10.1016/j.rcim.2019.04.006
10.1016/j.eswa.2015.06.004
10.1109/RAMS48097.2021.9605799
10.1007/s10951-018-0579-8
10.1016/j.compchemeng.2017.05.004
10.1109/TSMC.2019.2907575
10.1016/j.engappai.2021.104307
10.1109/WSC52266.2021.9715373
10.1016/j.jmsy.2021.09.018
10.1016/j.rcim.2020.101932
10.1049/iet-cim.2018.0009
10.1007/s10479-007-0272-3
10.23919/ANNSIM52504.2021.9552113
10.1007/s11356-022-21008-0
10.1016/j.future.2018.10.013
10.1016/j.cie.2020.106778
10.1016/j.ifacol.2019.11.385
ContentType Journal Article
Copyright 2025 Elsevier Ltd
Copyright_xml – notice: 2025 Elsevier Ltd
DBID AAYXX
CITATION
DOI 10.1016/j.cor.2025.107284
DatabaseName CrossRef
DatabaseTitle CrossRef
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
Computer Science
Business
ExternalDocumentID 10_1016_j_cor_2025_107284
S0305054825003132
GroupedDBID --K
--M
-~X
.DC
.~1
0R~
186
1B1
1OL
1RT
1~.
1~5
29F
4.4
457
4G.
5GY
5VS
6J9
7-5
71M
8P~
9JN
9JO
AAAKF
AAAKG
AABNK
AAEDT
AAEDW
AAFJI
AAIKJ
AAKOC
AALRI
AAOAW
AAQXK
AARIN
AATTM
AAXKI
AAXUO
AAYFN
AAYWO
ABAOU
ABBOA
ABDPE
ABEFU
ABFNM
ABFRF
ABJNI
ABMAC
ABMMH
ABUCO
ABWVN
ABXDB
ACDAQ
ACGFO
ACGFS
ACLOT
ACNCT
ACNNM
ACRLP
ACRPL
ACVFH
ACZNC
ADBBV
ADCNI
ADEZE
ADGUI
ADJOM
ADMUD
ADNMO
AEBSH
AEFWE
AEHXG
AEIPS
AEKER
AENEX
AEUPX
AFFNX
AFJKZ
AFPUW
AFTJW
AGHFR
AGQPQ
AGUBO
AGYEJ
AHHHB
AHZHX
AI.
AIALX
AIEXJ
AIGII
AIGVJ
AIIUN
AIKHN
AITUG
AKBMS
AKRWK
AKYEP
ALMA_UNASSIGNED_HOLDINGS
AMRAJ
ANKPU
AOMHK
AOUOD
APLSM
APXCP
ARUGR
ASPBG
AVARZ
AVWKF
AXJTR
AZFZN
BKOJK
BKOMP
BLXMC
CS3
DU5
EBS
EFJIC
EFKBS
EFLBG
EJD
EO8
EO9
EP2
EP3
FDB
FEDTE
FGOYB
FIRID
FNPLU
FYGXN
G-Q
GBLVA
GBOLZ
HAMUX
HVGLF
HZ~
H~9
IHE
J1W
KOM
LY1
M41
MHUIS
MO0
MS~
O-L
O9-
OAUVE
OZT
P-8
P-9
P2P
PC.
PQQKQ
PRBVW
Q38
R2-
ROL
RPZ
RXW
SDF
SDG
SDP
SDS
SES
SEW
SPC
SPCBC
SSB
SSD
SSO
SSV
SSW
SSZ
T5K
TAE
TN5
U5U
UPT
VH1
WUQ
XPP
ZMT
~02
~G-
~HD
9DU
AAYXX
CITATION
ID FETCH-LOGICAL-c251t-9c645d31458f1eca8670db007eb8f9adab221f66e85cf1cf96f65db1c607ee173
ISICitedReferencesCount 0
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001578084900001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 0305-0548
IngestDate Sat Nov 29 06:51:52 EST 2025
Sat Nov 15 16:52:43 EST 2025
IsPeerReviewed true
IsScholarly true
Keywords Zero-Inventory Production-scheduling
Mixed-integer non-linear programming
Online processors’ scheduling
Genetic Algorithm
Dispatching rules
Performance measurement
Mixed-integer linear programming
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c251t-9c645d31458f1eca8670db007eb8f9adab221f66e85cf1cf96f65db1c607ee173
ORCID 0000-0003-2667-0398
0000-0002-7682-7077
ParticipantIDs crossref_primary_10_1016_j_cor_2025_107284
elsevier_sciencedirect_doi_10_1016_j_cor_2025_107284
PublicationCentury 2000
PublicationDate January 2026
2026-01-00
PublicationDateYYYYMMDD 2026-01-01
PublicationDate_xml – month: 01
  year: 2026
  text: January 2026
PublicationDecade 2020
PublicationTitle Computers & operations research
PublicationYear 2026
Publisher Elsevier Ltd
Publisher_xml – name: Elsevier Ltd
References Benmansour, Braun, Hanafi (b0185) 2019; 22
Wu, Sun (b0105) 2018; 172
Lyu, Lin, Guo, Huang (b0015) 2020; 64
Shahriari, Shoja, Zade, Barak, Sharifi (b0215) 2016; 12
Sharifi, M., Taghipour, S., 2020. Joint optimizing the Production Sequence and Maintenance Plan for a Single-Machine Multi-Failure System. 2020 Annual Reliability and Maintainability Symposium (RAMS), IEEE; 2020, p. 1–6. doi:10.1109/RAMS48030.2020.9153629.
Braun, Chung, Graham (b0170) 2014; 17
Sharifi, Taghipour (b0265) 2021; 106
Bazargan-Lari, Taghipour, Zaretalab, Sharifi (b0235) 2022
Bazargan-Lari, Taghipour, Zaretalab, Sharifi (b0245) 2022
Takeda Berger, Zanella, Frazzon (b0135) 2019; 52
Xie, Gao, Peng, Li, Li (b0080) 2019; 1
Luo (b0120) 2020; 91
Rokhforoz, Fink (b0025) 2021; 59
Denkena, Schinkel, Pirnay, Wilmsmeier (b0130) 2021; 33
Sharifi, M., Taghipour, S., 2021. Joint Optimization of the Production Scheduling, Maintenance Activities, and Inventory Level for a Degrading Flexible Job-Shop Manufacturing System. 2021 Annual Reliability and Maintainability Symposium (RAMS), IEEE; 2021, p. 1–7. doi:10.1109/RAMS48097.2021.9605799.
Dereniowski, Kubiak (b0195) 2020; 282
Wang, Luo, Liu, Yue (b0255) 2018; 48
Ravi, Tunçel (b0160) 2020; 159–160
Eyerman, Eeckhout (b0165) 2010; 38
Sharifi, M., Abhari, A., Taghipour, S., 2021. A Queueing Model for Video Analytics Applications of Smart Cities. 2021 Winter Simulation Conference (WSC), IEEE; 2021, p. 1–10. doi:10.1109/WSC52266.2021.9715373.
Ghaleb, Taghipour, Zolfagharinia (b0240) 2021; 61
Yin, Li, Gao, Lu, Zhang (b0205) 2017; 13
Ghaleb, Taghipour, Sharifi, Zolfagharinia (b0220) 2020; 143
Li, Lei (b0125) 2021; 103
Mokhtari, Hasani (b0100) 2017; 104
Mashud, Roy, Chakrabortty, Tseng, Pervin (b0010) 2022
Pandey, Singh, Gebreegziabher, Kemal (b0180) 2016; 04
Sharifi, M., Abhari, A., Taghipour, S., 2021. Modeling Real-Time Application Processor Scheduling for Fog Computing. 2021 Annual Modeling and Simulation Conference (ANNSIM), IEEE; 2021, p. 1–12. doi:10.23919/ANNSIM52504.2021.9552113.
Dai, Tang, Giret, Salido (b0110) 2019; 59
Qamar, Hall, Chicksand, Collinson (b0005) 2020; 31
Yang, Liu, Li, Xu (b0145) 2021; 136
Ghaleb, Zolfagharinia, Taghipour (b0230) 2020; 123
Gao, Suganthan, Chua, Chong, Cai, Pan (b0090) 2015; 42
Muhuri, Rauniyar, Nath (b0190) 2019; 93
Fu, Zhou, Guo, Qi (b0260) 2020; 50
Li, Gao (b0095) 2016; 174
Armstrong, Gao, Lei (b0150) 2008; 159
Ji, Gu (b0030) 2021; 145
Shen, Yao (b0085) 2015; 298
Chen, Yang, Li, Wang (b0115) 2020; 149
Bathrinath, Saravanasankar, Mahapatra, Singh, Ponnambalam (b0175) 2016; 230
Chen, Liu, Chou (b0250) 2013; 43
Tang, Dai, Salido, Giret (b0210) 2016; 81
Jiang, Zhang, Chen, Chen, Lee (b0020) 2021; 876
Rokhforoz (10.1016/j.cor.2025.107284_b0025) 2021; 59
Muhuri (10.1016/j.cor.2025.107284_b0190) 2019; 93
Li (10.1016/j.cor.2025.107284_b0125) 2021; 103
Bathrinath (10.1016/j.cor.2025.107284_b0175) 2016; 230
Pandey (10.1016/j.cor.2025.107284_b0180) 2016; 04
Sharifi (10.1016/j.cor.2025.107284_b0265) 2021; 106
Eyerman (10.1016/j.cor.2025.107284_b0165) 2010; 38
Braun (10.1016/j.cor.2025.107284_b0170) 2014; 17
Li (10.1016/j.cor.2025.107284_b0095) 2016; 174
Chen (10.1016/j.cor.2025.107284_b0115) 2020; 149
Bazargan-Lari (10.1016/j.cor.2025.107284_b0235) 2022
Bazargan-Lari (10.1016/j.cor.2025.107284_b0245) 2022
Xie (10.1016/j.cor.2025.107284_b0080) 2019; 1
Mashud (10.1016/j.cor.2025.107284_b0010) 2022
Gao (10.1016/j.cor.2025.107284_b0090) 2015; 42
10.1016/j.cor.2025.107284_b0140
Jiang (10.1016/j.cor.2025.107284_b0020) 2021; 876
Shahriari (10.1016/j.cor.2025.107284_b0215) 2016; 12
Luo (10.1016/j.cor.2025.107284_b0120) 2020; 91
Ghaleb (10.1016/j.cor.2025.107284_b0240) 2021; 61
Yin (10.1016/j.cor.2025.107284_b0205) 2017; 13
Chen (10.1016/j.cor.2025.107284_b0250) 2013; 43
Fu (10.1016/j.cor.2025.107284_b0260) 2020; 50
Wu (10.1016/j.cor.2025.107284_b0105) 2018; 172
Tang (10.1016/j.cor.2025.107284_b0210) 2016; 81
Denkena (10.1016/j.cor.2025.107284_b0130) 2021; 33
10.1016/j.cor.2025.107284_b0200
10.1016/j.cor.2025.107284_b0225
Wang (10.1016/j.cor.2025.107284_b0255) 2018; 48
Ghaleb (10.1016/j.cor.2025.107284_b0220) 2020; 143
Mokhtari (10.1016/j.cor.2025.107284_b0100) 2017; 104
Dai (10.1016/j.cor.2025.107284_b0110) 2019; 59
Ghaleb (10.1016/j.cor.2025.107284_b0230) 2020; 123
Benmansour (10.1016/j.cor.2025.107284_b0185) 2019; 22
10.1016/j.cor.2025.107284_b0155
Takeda Berger (10.1016/j.cor.2025.107284_b0135) 2019; 52
Yang (10.1016/j.cor.2025.107284_b0145) 2021; 136
Lyu (10.1016/j.cor.2025.107284_b0015) 2020; 64
Qamar (10.1016/j.cor.2025.107284_b0005) 2020; 31
Shen (10.1016/j.cor.2025.107284_b0085) 2015; 298
Ji (10.1016/j.cor.2025.107284_b0030) 2021; 145
Armstrong (10.1016/j.cor.2025.107284_b0150) 2008; 159
Ravi (10.1016/j.cor.2025.107284_b0160) 2020; 159–160
Dereniowski (10.1016/j.cor.2025.107284_b0195) 2020; 282
References_xml – volume: 298
  start-page: 198
  year: 2015
  end-page: 224
  ident: b0085
  article-title: Mathematical modeling and multi-objective evolutionary algorithms applied to dynamic flexible job shop scheduling problems
  publication-title: Inf. Sci. (NY)
– volume: 31
  start-page: 723
  year: 2020
  end-page: 738
  ident: b0005
  article-title: Quality and flexibility performance trade-offs between lean and agile manufacturing firms in the automotive industry
  publication-title: Production Planning & Control
– volume: 59
  start-page: 596
  year: 2021
  end-page: 606
  ident: b0025
  article-title: Distributed joint dynamic maintenance and production scheduling in manufacturing systems: Framework based on model predictive control and Benders decomposition
  publication-title: J. Manuf. Syst.
– volume: 17
  start-page: 399
  year: 2014
  end-page: 403
  ident: b0170
  article-title: Single-processor scheduling with time restrictions
  publication-title: J. Sched.
– volume: 106
  year: 2021
  ident: b0265
  article-title: Optimal production and maintenance scheduling for a degrading multi-failure modes single-machine production environment
  publication-title: Appl. Soft. Comput.
– volume: 103
  year: 2021
  ident: b0125
  article-title: An imperialist competitive algorithm with feedback for energy-efficient flexible job shop scheduling with transportation and sequence-dependent setup times
  publication-title: Eng. Appl. Artif. Intel.
– volume: 43
  start-page: 1077
  year: 2013
  end-page: 1090
  ident: b0250
  article-title: Integrated short-haul airline crew scheduling using multiobjective optimization genetic algorithms
  publication-title: IEEE Trans. Syst. Man Cybern. Syst.
– volume: 230
  start-page: 1114
  year: 2016
  end-page: 1126
  ident: b0175
  article-title: An improved meta-heuristic approach for solving identical parallel processor scheduling problem
  publication-title: Proc. Inst. Mech. Eng. B J. Eng. Manuf.
– volume: 04
  start-page: 146
  year: 2016
  end-page: 159
  ident: b0180
  article-title: Chronically evaluated highest instantaneous priority next: a novel algorithm for processor scheduling
  publication-title: Journal of Computer and Communications
– volume: 13
  start-page: 15
  year: 2017
  end-page: 30
  ident: b0205
  article-title: A novel mathematical model and multi-objective method for the low-carbon flexible job shop scheduling problem
  publication-title: Sustainable Computing: Informatics and Systems
– volume: 38
  start-page: 91
  year: 2010
  end-page: 102
  ident: b0165
  article-title: Probabilistic job symbiosis modeling for SMT processor scheduling
  publication-title: ACM SIGARCH Computer Architecture News
– volume: 93
  start-page: 702
  year: 2019
  end-page: 726
  ident: b0190
  article-title: On arrival scheduling of real-time precedence constrained tasks on multi-processor systems using genetic algorithm
  publication-title: Futur. Gener. Comput. Syst.
– volume: 149
  year: 2020
  ident: b0115
  article-title: A self-learning genetic algorithm based on reinforcement learning for flexible job-shop scheduling problem
  publication-title: Comput. Ind. Eng.
– volume: 159–160
  year: 2020
  ident: b0160
  article-title: Approximation ratio of LD algorithm for multi-processor scheduling and the Coffman–Sethi conjecture
  publication-title: Inf. Process. Lett.
– reference: Sharifi, M., Abhari, A., Taghipour, S., 2021. Modeling Real-Time Application Processor Scheduling for Fog Computing. 2021 Annual Modeling and Simulation Conference (ANNSIM), IEEE; 2021, p. 1–12. doi:10.23919/ANNSIM52504.2021.9552113.
– reference: Sharifi, M., Taghipour, S., 2020. Joint optimizing the Production Sequence and Maintenance Plan for a Single-Machine Multi-Failure System. 2020 Annual Reliability and Maintainability Symposium (RAMS), IEEE; 2020, p. 1–6. doi:10.1109/RAMS48030.2020.9153629.
– year: 2022
  ident: b0235
  article-title: Production scheduling optimization for a parallel machine subject to physical distancing due to COVID-19
  publication-title: Oper. Manag. Res.
– volume: 52
  start-page: 1343
  year: 2019
  end-page: 1348
  ident: b0135
  article-title: Towards a data-driven predictive-reactive production scheduling approach based on inventory availability
  publication-title: IFAC-PapersOnLine
– volume: 143
  year: 2020
  ident: b0220
  article-title: Integrated production and maintenance scheduling for a single degrading machine with deterioration-based failures
  publication-title: Comput. Ind. Eng.
– volume: 159
  start-page: 395
  year: 2008
  end-page: 414
  ident: b0150
  article-title: A zero-inventory production and distribution problem with a fixed customer sequence
  publication-title: Ann. Oper. Res.
– volume: 282
  start-page: 464
  year: 2020
  end-page: 477
  ident: b0195
  article-title: Shared processor scheduling of multiprocessor jobs
  publication-title: Eur. J. Oper. Res.
– volume: 1
  start-page: 67
  year: 2019
  end-page: 77
  ident: b0080
  article-title: Review on flexible job shop scheduling
  publication-title: IET Collab. Intell. Manuf.
– volume: 48
  start-page: 1826
  year: 2018
  end-page: 1837
  ident: b0255
  article-title: Permutation flow shop scheduling with batch delivery to multiple customers in supply chains
  publication-title: IEEE Trans. Syst. Man Cybern. Syst.
– volume: 59
  start-page: 143
  year: 2019
  end-page: 157
  ident: b0110
  article-title: Multi-objective optimization for energy-efficient flexible job shop scheduling problem with transportation constraints
  publication-title: Rob. Comput. Integr. Manuf.
– volume: 33
  start-page: 100
  year: 2021
  end-page: 114
  ident: b0130
  article-title: Quantum algorithms for process parallel flexible job shop scheduling
  publication-title: CIRP J. Manuf. Sci. Technol.
– reference: Sharifi, M., Abhari, A., Taghipour, S., 2021. A Queueing Model for Video Analytics Applications of Smart Cities. 2021 Winter Simulation Conference (WSC), IEEE; 2021, p. 1–10. doi:10.1109/WSC52266.2021.9715373.
– volume: 12
  year: 2016
  ident: b0215
  article-title: JIT single machine scheduling problem with periodic preventive maintenance
  publication-title: J. Indus. Eng. Int.
– volume: 91
  year: 2020
  ident: b0120
  article-title: Dynamic scheduling for flexible job shop with new job insertions by deep reinforcement learning
  publication-title: Appl. Soft Comput.
– volume: 50
  start-page: 5037
  year: 2020
  end-page: 5048
  ident: b0260
  article-title: Scheduling dual-objective stochastic hybrid flow shop with deteriorating jobs via bi-population evolutionary algorithm
  publication-title: IEEE Trans. Syst. Man Cybern. Syst.
– volume: 172
  start-page: 3249
  year: 2018
  end-page: 3264
  ident: b0105
  article-title: A green scheduling algorithm for flexible job shop with energy-saving measures
  publication-title: J. Clean. Prod.
– volume: 104
  start-page: 339
  year: 2017
  end-page: 352
  ident: b0100
  article-title: An energy-efficient multi-objective optimization for flexible job-shop scheduling problem
  publication-title: Comput. Chem. Eng.
– volume: 876
  start-page: 59
  year: 2021
  end-page: 69
  ident: b0020
  article-title: An improved algorithm for a two-stage production scheduling problem with an outsourcing option
  publication-title: Theor. Comput. Sci.
– volume: 42
  start-page: 7652
  year: 2015
  end-page: 7663
  ident: b0090
  article-title: A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion
  publication-title: Expert Syst. Appl.
– reference: Sharifi, M., Taghipour, S., 2021. Joint Optimization of the Production Scheduling, Maintenance Activities, and Inventory Level for a Degrading Flexible Job-Shop Manufacturing System. 2021 Annual Reliability and Maintainability Symposium (RAMS), IEEE; 2021, p. 1–7. doi:10.1109/RAMS48097.2021.9605799.
– volume: 64
  year: 2020
  ident: b0015
  article-title: Towards Zero-Warehousing Smart Manufacturing from Zero-Inventory Just-In-Time production
  publication-title: Rob. Comput. Integr. Manuf.
– volume: 22
  start-page: 465
  year: 2019
  end-page: 471
  ident: b0185
  article-title: The single-processor scheduling problem with time restrictions: complexity and related problems
  publication-title: J. Sched.
– volume: 61
  start-page: 423
  year: 2021
  end-page: 449
  ident: b0240
  article-title: Real-time integrated production-scheduling and maintenance-planning in a flexible job shop with machine deterioration and condition-based maintenance
  publication-title: J. Manuf. Syst.
– year: 2022
  ident: b0245
  article-title: Planning and scheduling of a parallel-machine production system subject to disruptions and physical distancing
  publication-title: IMA J. Manag. Math.
– volume: 81
  start-page: 82
  year: 2016
  end-page: 95
  ident: b0210
  article-title: Energy-efficient dynamic scheduling for a flexible flow shop using an improved particle swarm optimization
  publication-title: Comput. Ind.
– volume: 123
  year: 2020
  ident: b0230
  article-title: Real-time production scheduling in the Industry-4.0 context: addressing uncertainties in job arrivals and machine breakdowns
  publication-title: Comput. Oper. Res.
– volume: 136
  year: 2021
  ident: b0145
  article-title: Integrated production and transportation scheduling with order-dependent inventory holding costs
  publication-title: Comput. Oper. Res.
– year: 2022
  ident: b0010
  article-title: An optimum balance among the reduction in ordering cost, product deterioration and carbon emissions: a sustainable green warehouse
  publication-title: Environ. Sci. Pollut. Res.
– volume: 174
  start-page: 93
  year: 2016
  end-page: 110
  ident: b0095
  article-title: An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem
  publication-title: Int. J. Prod. Econ.
– volume: 145
  year: 2021
  ident: b0030
  article-title: Integration of scheduling and control for batch process based on generalized Benders decomposition approach with genetic algorithm
  publication-title: Comput. Chem. Eng.
– volume: 174
  start-page: 93
  year: 2016
  ident: 10.1016/j.cor.2025.107284_b0095
  article-title: An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem
  publication-title: Int. J. Prod. Econ.
  doi: 10.1016/j.ijpe.2016.01.016
– volume: 136
  year: 2021
  ident: 10.1016/j.cor.2025.107284_b0145
  article-title: Integrated production and transportation scheduling with order-dependent inventory holding costs
  publication-title: Comput. Oper. Res.
  doi: 10.1016/j.cor.2021.105477
– volume: 91
  year: 2020
  ident: 10.1016/j.cor.2025.107284_b0120
  article-title: Dynamic scheduling for flexible job shop with new job insertions by deep reinforcement learning
  publication-title: Appl. Soft Comput.
  doi: 10.1016/j.asoc.2020.106208
– volume: 123
  year: 2020
  ident: 10.1016/j.cor.2025.107284_b0230
  article-title: Real-time production scheduling in the Industry-4.0 context: addressing uncertainties in job arrivals and machine breakdowns
  publication-title: Comput. Oper. Res.
  doi: 10.1016/j.cor.2020.105031
– volume: 298
  start-page: 198
  year: 2015
  ident: 10.1016/j.cor.2025.107284_b0085
  article-title: Mathematical modeling and multi-objective evolutionary algorithms applied to dynamic flexible job shop scheduling problems
  publication-title: Inf. Sci. (NY)
  doi: 10.1016/j.ins.2014.11.036
– volume: 33
  start-page: 100
  year: 2021
  ident: 10.1016/j.cor.2025.107284_b0130
  article-title: Quantum algorithms for process parallel flexible job shop scheduling
  publication-title: CIRP J. Manuf. Sci. Technol.
  doi: 10.1016/j.cirpj.2021.03.006
– volume: 876
  start-page: 59
  year: 2021
  ident: 10.1016/j.cor.2025.107284_b0020
  article-title: An improved algorithm for a two-stage production scheduling problem with an outsourcing option
  publication-title: Theor. Comput. Sci.
  doi: 10.1016/j.tcs.2021.05.022
– volume: 59
  start-page: 596
  year: 2021
  ident: 10.1016/j.cor.2025.107284_b0025
  article-title: Distributed joint dynamic maintenance and production scheduling in manufacturing systems: Framework based on model predictive control and Benders decomposition
  publication-title: J. Manuf. Syst.
  doi: 10.1016/j.jmsy.2021.04.010
– ident: 10.1016/j.cor.2025.107284_b0225
  doi: 10.1109/RAMS48030.2020.9153629
– volume: 81
  start-page: 82
  year: 2016
  ident: 10.1016/j.cor.2025.107284_b0210
  article-title: Energy-efficient dynamic scheduling for a flexible flow shop using an improved particle swarm optimization
  publication-title: Comput. Ind.
  doi: 10.1016/j.compind.2015.10.001
– volume: 143
  year: 2020
  ident: 10.1016/j.cor.2025.107284_b0220
  article-title: Integrated production and maintenance scheduling for a single degrading machine with deterioration-based failures
  publication-title: Comput. Ind. Eng.
  doi: 10.1016/j.cie.2020.106432
– volume: 48
  start-page: 1826
  year: 2018
  ident: 10.1016/j.cor.2025.107284_b0255
  article-title: Permutation flow shop scheduling with batch delivery to multiple customers in supply chains
  publication-title: IEEE Trans. Syst. Man Cybern. Syst.
  doi: 10.1109/TSMC.2017.2720178
– volume: 31
  start-page: 723
  year: 2020
  ident: 10.1016/j.cor.2025.107284_b0005
  article-title: Quality and flexibility performance trade-offs between lean and agile manufacturing firms in the automotive industry
  publication-title: Production Planning & Control
  doi: 10.1080/09537287.2019.1681534
– volume: 17
  start-page: 399
  year: 2014
  ident: 10.1016/j.cor.2025.107284_b0170
  article-title: Single-processor scheduling with time restrictions
  publication-title: J. Sched.
  doi: 10.1007/s10951-013-0342-0
– volume: 38
  start-page: 91
  year: 2010
  ident: 10.1016/j.cor.2025.107284_b0165
  article-title: Probabilistic job symbiosis modeling for SMT processor scheduling
  publication-title: ACM SIGARCH Computer Architecture News
  doi: 10.1145/1735970.1736033
– volume: 43
  start-page: 1077
  year: 2013
  ident: 10.1016/j.cor.2025.107284_b0250
  article-title: Integrated short-haul airline crew scheduling using multiobjective optimization genetic algorithms
  publication-title: IEEE Trans. Syst. Man Cybern. Syst.
  doi: 10.1109/TSMC.2012.2234943
– volume: 04
  start-page: 146
  year: 2016
  ident: 10.1016/j.cor.2025.107284_b0180
  article-title: Chronically evaluated highest instantaneous priority next: a novel algorithm for processor scheduling
  publication-title: Journal of Computer and Communications
  doi: 10.4236/jcc.2016.44013
– year: 2022
  ident: 10.1016/j.cor.2025.107284_b0235
  article-title: Production scheduling optimization for a parallel machine subject to physical distancing due to COVID-19
  publication-title: Oper. Manag. Res.
– volume: 230
  start-page: 1114
  year: 2016
  ident: 10.1016/j.cor.2025.107284_b0175
  article-title: An improved meta-heuristic approach for solving identical parallel processor scheduling problem
  publication-title: Proc. Inst. Mech. Eng. B J. Eng. Manuf.
  doi: 10.1177/0954405414564410
– year: 2022
  ident: 10.1016/j.cor.2025.107284_b0245
  article-title: Planning and scheduling of a parallel-machine production system subject to disruptions and physical distancing
  publication-title: IMA J. Manag. Math.
– volume: 106
  year: 2021
  ident: 10.1016/j.cor.2025.107284_b0265
  article-title: Optimal production and maintenance scheduling for a degrading multi-failure modes single-machine production environment
  publication-title: Appl. Soft. Comput.
  doi: 10.1016/j.asoc.2021.107312
– volume: 145
  year: 2021
  ident: 10.1016/j.cor.2025.107284_b0030
  article-title: Integration of scheduling and control for batch process based on generalized Benders decomposition approach with genetic algorithm
  publication-title: Comput. Chem. Eng.
  doi: 10.1016/j.compchemeng.2020.107166
– volume: 172
  start-page: 3249
  year: 2018
  ident: 10.1016/j.cor.2025.107284_b0105
  article-title: A green scheduling algorithm for flexible job shop with energy-saving measures
  publication-title: J. Clean. Prod.
  doi: 10.1016/j.jclepro.2017.10.342
– volume: 282
  start-page: 464
  year: 2020
  ident: 10.1016/j.cor.2025.107284_b0195
  article-title: Shared processor scheduling of multiprocessor jobs
  publication-title: Eur. J. Oper. Res.
  doi: 10.1016/j.ejor.2019.09.033
– volume: 159–160
  year: 2020
  ident: 10.1016/j.cor.2025.107284_b0160
  article-title: Approximation ratio of LD algorithm for multi-processor scheduling and the Coffman–Sethi conjecture
  publication-title: Inf. Process. Lett.
– volume: 59
  start-page: 143
  year: 2019
  ident: 10.1016/j.cor.2025.107284_b0110
  article-title: Multi-objective optimization for energy-efficient flexible job shop scheduling problem with transportation constraints
  publication-title: Rob. Comput. Integr. Manuf.
  doi: 10.1016/j.rcim.2019.04.006
– volume: 42
  start-page: 7652
  year: 2015
  ident: 10.1016/j.cor.2025.107284_b0090
  article-title: A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2015.06.004
– ident: 10.1016/j.cor.2025.107284_b0140
  doi: 10.1109/RAMS48097.2021.9605799
– volume: 22
  start-page: 465
  year: 2019
  ident: 10.1016/j.cor.2025.107284_b0185
  article-title: The single-processor scheduling problem with time restrictions: complexity and related problems
  publication-title: J. Sched.
  doi: 10.1007/s10951-018-0579-8
– volume: 104
  start-page: 339
  year: 2017
  ident: 10.1016/j.cor.2025.107284_b0100
  article-title: An energy-efficient multi-objective optimization for flexible job-shop scheduling problem
  publication-title: Comput. Chem. Eng.
  doi: 10.1016/j.compchemeng.2017.05.004
– volume: 50
  start-page: 5037
  year: 2020
  ident: 10.1016/j.cor.2025.107284_b0260
  article-title: Scheduling dual-objective stochastic hybrid flow shop with deteriorating jobs via bi-population evolutionary algorithm
  publication-title: IEEE Trans. Syst. Man Cybern. Syst.
  doi: 10.1109/TSMC.2019.2907575
– volume: 103
  year: 2021
  ident: 10.1016/j.cor.2025.107284_b0125
  article-title: An imperialist competitive algorithm with feedback for energy-efficient flexible job shop scheduling with transportation and sequence-dependent setup times
  publication-title: Eng. Appl. Artif. Intel.
  doi: 10.1016/j.engappai.2021.104307
– ident: 10.1016/j.cor.2025.107284_b0200
  doi: 10.1109/WSC52266.2021.9715373
– volume: 61
  start-page: 423
  year: 2021
  ident: 10.1016/j.cor.2025.107284_b0240
  article-title: Real-time integrated production-scheduling and maintenance-planning in a flexible job shop with machine deterioration and condition-based maintenance
  publication-title: J. Manuf. Syst.
  doi: 10.1016/j.jmsy.2021.09.018
– volume: 64
  year: 2020
  ident: 10.1016/j.cor.2025.107284_b0015
  article-title: Towards Zero-Warehousing Smart Manufacturing from Zero-Inventory Just-In-Time production
  publication-title: Rob. Comput. Integr. Manuf.
  doi: 10.1016/j.rcim.2020.101932
– volume: 1
  start-page: 67
  year: 2019
  ident: 10.1016/j.cor.2025.107284_b0080
  article-title: Review on flexible job shop scheduling
  publication-title: IET Collab. Intell. Manuf.
  doi: 10.1049/iet-cim.2018.0009
– volume: 159
  start-page: 395
  year: 2008
  ident: 10.1016/j.cor.2025.107284_b0150
  article-title: A zero-inventory production and distribution problem with a fixed customer sequence
  publication-title: Ann. Oper. Res.
  doi: 10.1007/s10479-007-0272-3
– ident: 10.1016/j.cor.2025.107284_b0155
  doi: 10.23919/ANNSIM52504.2021.9552113
– volume: 13
  start-page: 15
  year: 2017
  ident: 10.1016/j.cor.2025.107284_b0205
  article-title: A novel mathematical model and multi-objective method for the low-carbon flexible job shop scheduling problem
  publication-title: Sustainable Computing: Informatics and Systems
– volume: 12
  year: 2016
  ident: 10.1016/j.cor.2025.107284_b0215
  article-title: JIT single machine scheduling problem with periodic preventive maintenance
  publication-title: J. Indus. Eng. Int.
– year: 2022
  ident: 10.1016/j.cor.2025.107284_b0010
  article-title: An optimum balance among the reduction in ordering cost, product deterioration and carbon emissions: a sustainable green warehouse
  publication-title: Environ. Sci. Pollut. Res.
  doi: 10.1007/s11356-022-21008-0
– volume: 93
  start-page: 702
  year: 2019
  ident: 10.1016/j.cor.2025.107284_b0190
  article-title: On arrival scheduling of real-time precedence constrained tasks on multi-processor systems using genetic algorithm
  publication-title: Futur. Gener. Comput. Syst.
  doi: 10.1016/j.future.2018.10.013
– volume: 149
  year: 2020
  ident: 10.1016/j.cor.2025.107284_b0115
  article-title: A self-learning genetic algorithm based on reinforcement learning for flexible job-shop scheduling problem
  publication-title: Comput. Ind. Eng.
  doi: 10.1016/j.cie.2020.106778
– volume: 52
  start-page: 1343
  year: 2019
  ident: 10.1016/j.cor.2025.107284_b0135
  article-title: Towards a data-driven predictive-reactive production scheduling approach based on inventory availability
  publication-title: IFAC-PapersOnLine
  doi: 10.1016/j.ifacol.2019.11.385
SSID ssj0000721
Score 2.4756055
Snippet •Considering a zero-inventory production-scheduling problem.•Presenting an MINLP model and linearizing it (turning it into a MILP model).•Designing an...
SourceID crossref
elsevier
SourceType Index Database
Publisher
StartPage 107284
SubjectTerms Dispatching rules
Genetic Algorithm
Mixed-integer linear programming
Mixed-integer non-linear programming
Online processors’ scheduling
Performance measurement
Zero-Inventory Production-scheduling
Title A novel mathematical model for the scheduling of a zero inventory production: an application of process scheduling in fog computing
URI https://dx.doi.org/10.1016/j.cor.2025.107284
Volume 185
WOSCitedRecordID wos001578084900001&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
journalDatabaseRights – providerCode: PRVESC
  databaseName: ScienceDirect
  issn: 0305-0548
  databaseCode: AIEXJ
  dateStart: 19950101
  customDbUrl:
  isFulltext: true
  dateEnd: 99991231
  titleUrlDefault: https://www.sciencedirect.com
  omitProxy: false
  ssIdentifier: ssj0000721
  providerName: Elsevier
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lj9MwELbKLkJw4FFALC_5wImqaPNyHG4RWgQcVggtUm-R49hLqm4Spd1q6ZVfxD9k_IhjFlZiD1yiKrKnaebrzHj8zRihV4QRzljMFHsqnMcl_NOzkvI5japYVJms6KHUh02kx8d0scg-TyY_h1qY7SptGnpxkXX_VdVwD5StSmevoW4nFG7AZ1A6XEHtcP0nxeezpt2K1ezMNWRVBSLqwBtHKYQVLXiYlSU8s9lO9O2s1vRzteXemS6wlvUBBsDb5dYMaVNc4IupFV9RV-9255vBGw4NEOzBEWsNs7YTvaXf2UZDLiGtmkfXsjYlRE09JhVOv9Ud_HSdqVUNpnvh5uSlmqQtXFm1q17snJ_58n29M7LAfi399EbopzdsWZdiFyamHedoshPP6MIKNjTnzP3hD0xqYgnqVL1fw-TNOPb33tuXfKJjKg4kuGUBIgolojAibqD9ME0yMKT7-cejxafR_ae62M8997CVrkmFl57j78GQF-Cc3Ed37coE5wZRD9BENFN0ayiMmKJ7gx6x9QdTdMfrZvkQ_cixRh72kYc18jAgD8NNPEIGtxIzrJCHHfLwiLy3mDXYw50abnHnC6kbEH2KHe4eoa_vj07efZjbMz7mHCLrzTzjJE6qKIgTKgPBGSXpYQWuIBUllRmrWBmGgSRE0ITLgMuMSJJUZcAJDBFBGj1Ge03biCcIy5AGvCxFEsGbjShjEB1nTFARUFLxKjxAr4eXXXSmlUtxpXoPUDyoo7CxqIkxC4DW1dOeXuc7nqHbI-Kfo71Nfy5eoJt8u6nX_UuLq1_Om7Bv
linkProvider Elsevier
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%3Ajournal&rft.genre=article&rft.atitle=A+novel+mathematical+model+for+the+scheduling+of+a+zero+inventory+production%3A+an+application+of+process+scheduling+in+fog+computing&rft.jtitle=Computers+%26+operations+research&rft.au=Sharifi%2C+Mani&rft.au=Taghipour%2C+Sharareh&rft.au=Abhari%2C+Abdolreza&rft.au=Rysz%2C+Maciej&rft.date=2026-01-01&rft.issn=0305-0548&rft.volume=185&rft.spage=107284&rft_id=info:doi/10.1016%2Fj.cor.2025.107284&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_cor_2025_107284
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0305-0548&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0305-0548&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0305-0548&client=summon