Incorporating order acceptance, pricing and equity considerations in the scheduling of cloud manufacturing systems: matheuristic methods
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F21%3A00343706" target="_blank" >RIV/68407700:21730/21:00343706 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1080/00207543.2020.1806370" target="_blank" >https://doi.org/10.1080/00207543.2020.1806370</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/00207543.2020.1806370" target="_blank" >10.1080/00207543.2020.1806370</a>
Alternative languages
Result language
angličtina
Original language name
Incorporating order acceptance, pricing and equity considerations in the scheduling of cloud manufacturing systems: matheuristic methods
Original language description
Rooted from the Industry 4.0 principles, Cloud Manufacturing (CMfg) is a novel customer-oriented manufacturing norm, which can assist enterprises to withstand in the nowadays highly volatile and competitive market. CMfg systems comprise two separate parties, namely, customers and factories, with independent individuals. In this regard, considering the utilities of both customers and factories and establishing the equity amongst their individuals are of particular importance for the survival and flourishment of CMfg systems. Furthermore, due to the limited capacity of resources, tightness of due dates, and customers' cost expectations, all orders may not be accepted in CMfg systems. Accordingly, this paper aims to explore a scheduling problem in a CMfg system. A multi-objective mathematical model is presented for the problem, which can determine the acceptance or rejection of orders, set prices, and schedule them in an integrated manner to maximise the customers and factories' utilities, and enhance the equity among their members. Due to the high complexity of the problem, two matheuristic methods based on the Multi-Objective Grey Wolf Optimizer (MOGWO) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) are developed. An extensive computational experiment is carried out to validate the proposed matheuristic methods and evaluate their performance. Moreover, some guidance is presented for managers by conducting a sensitivity analysis.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LL1902" target="_blank" >LL1902: Powering SMT Solvers by Machine Learning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Production Research
ISSN
0020-7543
e-ISSN
1366-588X
Volume of the periodical
59
Issue of the periodical within the volume
7
Country of publishing house
GB - UNITED KINGDOM
Number of pages
19
Pages from-to
2009-2027
UT code for WoS article
000559869000001
EID of the result in the Scopus database
2-s2.0-85089477749