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Game theory based real-time multi-objective flexible job shop scheduling considering environmental impact
Northwestern Polytech University, Peoples R China.
Northwestern Polytech University, Peoples R China.
Linköping University, Department of Management and Engineering. Linköping University, Faculty of Science & Engineering. University of Vaasa, Finland.ORCID iD: 0000-0001-8006-3236
2017 (English)In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 167, 665-679 p.Article in journal (Refereed) Published
Abstract [en]

Production scheduling greatly contributes to optimising the allocation of processes, reducing resource and energy consumption, lowering production costs and alleviating environmental pollution. It is an effective way to progress towards green manufacturing. With the extensive use of the Internet of Things in the manufacturing shop floor, a huge amount of real-time data is created. A typical challenge is how to achieve the real-time data-driven optimisation for the manufacturing shop floor to improve energy efficiency and production efficiency. To address this problem, a dynamic game theory based two-layer scheduling method was developed to reduce makespan, the total workload of machines and energy consumption to achieve real-time multi-objective flexible job shop scheduling. To obtain an optimal solution, a sub-game perfect Nash equilibrium solution was designed. Then, a case study was employed to analyse the performance of the proposed method. The results showed that the makespan, the total workload of machines and energy consumption were reduced by 4.5%, 8.75%, and 9.3% respectively. These improvements can contribute to sustainable development and cleaner production of manufacturing industry. (C) 2017 Elsevier Ltd. All rights reserved.

Place, publisher, year, edition, pages
ELSEVIER SCI LTD , 2017. Vol. 167, 665-679 p.
Keyword [en]
Real-time data; Multi-objective; Flexible job shop scheduling; Dynamic game theory
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:liu:diva-142826DOI: 10.1016/j.jclepro.2017.08.068ISI: 000413128100058OAI: oai:DiVA.org:liu-142826DiVA: diva2:1154967
Note

Funding Agencies|National Science Foundation of China [51675441]; Fundamental Research Funds for the Central Universities [3102017jc04001]; 111 Project [B13044]; Circularis (Circular Economy through Innovating Design) project - Vinnova - Swedens Innovation Agency [2016-03267]; Simon (New Application of AI for Services in Maintenance towards a Circular Economy) project - Vinnova - Swedens Innovation Agency [2017-01649]

Available from: 2017-11-06 Created: 2017-11-06 Last updated: 2017-11-06

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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