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International Journal of Production Research Volume 50, 2012 - Issue 18
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Original Articles

Optimal process plan selection in networked based manufacturing using game-theoretic approach

V.K. Manupati Department of Industrial Engineering and Management, Indian Institute of Technology Kharagpur, Kharagpur-721302, West Bengal, India
,
Sujay Deo Department of Mechanical Engineering, Indian Institute of Technology Kharagpur, Kharagpur-721302, West Bengal, India
,
N. Cheikhrouhou EPFL, Ecole Polytechnique Federale De Lausanne, France
&
M.K. Tiwari Department of Industrial Engineering and Management, Indian Institute of Technology Kharagpur, Kharagpur-721302, West Bengal, IndiaCorrespondence[email protected]
Pages 5239-5258 | Received 05 Nov 2011, Accepted 30 Mar 2012, Published online: 14 May 2012

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V. K. Manupati, Tobias Schoenherr, M. Ramkumar, Stephan M. Wagner, Sai Krishna Pabba & R. Inder Raj Singh. (2020) A blockchain-based approach for a multi-echelon sustainable supply chain. International Journal of Production Research 58:7, pages 2222-2241.
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Jianping Dou, Jun Li & Chun Su. (2018) A discrete particle swarm optimisation for operation sequencing in CAPP. International Journal of Production Research 56:11, pages 3795-3814.
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S.P. Leo Kumar, J. Jerald & S. Kumanan. (2014) An intelligent process planning system for micro turn-mill parts. International Journal of Production Research 52:20, pages 6052-6075.
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Sonia Mahjoub & Jean-Claude Hennet. (2014) Manufacturers’ coalition under a price elastic market – a quadratic production game approach. International Journal of Production Research 52:12, pages 3568-3582.
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Umut Tosun, Tansel Dokeroglu & Ahmet Cosar. (2013) A robust Island Parallel Genetic Algorithm for the Quadratic Assignment Problem. International Journal of Production Research 51:14, pages 4117-4133.
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Articles from other publishers (19)

Gulver Karamemis, Jiayuan Zhang & Yuwen Chen. (2023) Consignment and turnkey sourcing and outsourcing analysis for a three-player supply chain in various power dynamics. European Journal of Operational Research 311:1, pages 125-138.
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Mansour Abedian, Javid Jouzdani, AmirHossein Karimpour & Maryam Hejazi. (2022) A framework for accessing the equilibrium point of a multi-objective decision-making (MODM): a case study. Soft Computing 27:6, pages 3151-3167.
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Veerababu Ramakurthi, V.K. Manupati, José Machado, Leonilde Varela & Suresh Babu. (2022) An innovative approach for resource sharing and scheduling in a sustainable distributed manufacturing system. Advanced Engineering Informatics 52, pages 101620.
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Veera Babu Ramakurthi, V. K. Manupati, José Machado & Leonilde Varela. (2021) A Hybrid Multi-Objective Evolutionary Algorithm-Based Semantic Foundation for Sustainable Distributed Manufacturing Systems. Applied Sciences 11:14, pages 6314.
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Pengyu Yan, Hongru Miao, Ada Che & Kaize Yu. (2021) Nash-equilibrium algorithm and incentive protocol for a decentralized decision and scheduling problem in sustainable electroplating plants. Computers & Operations Research 128, pages 105130.
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Chi-Shiuan Lin, Pei-Yi Li, Jun-Min Wei & Muh-Cherng Wu. (2020) Integration of process planning and scheduling for distributed flexible job shops. Computers & Operations Research 124, pages 105053.
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Daniela Carlucci, Paolo Renna, Sergio Materi & Giovanni Schiuma. (2020) Intelligent decision-making model based on minority game for resource allocation in cloud manufacturing. Management Decision 58:11, pages 2305-2325.
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Jin Wang, Jiahao Yang, Yingfeng Zhang, Shan Ren & Yang Liu. (2020) Infinitely repeated game based real-time scheduling for low-carbon flexible job shop considering multi-time periods. Journal of Cleaner Production 247, pages 119093.
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Guang-hui Zhou, Chang-le Tian, Jun-jie Zhang, Feng-tian Chang & Qi Lu. (2018) Multi-objective process route optimization considering carbon emissions. The International Journal of Advanced Manufacturing Technology 96:1-4, pages 1195-1213.
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M.B.S. Sreekara Reddy, Ch. Ratnam, G. Rajyalakshmi & V.K. Manupati. (2018) An effective hybrid multi objective evolutionary algorithm for solving real time event in flexible job shop scheduling problem. Measurement 114, pages 78-90.
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M.B.S. Sreekara Reddy, C.h. Ratnam, Rajeev Agrawal, M.L.R. Varela, Ila Sharma & V.K. Manupati. (2017) Investigation of reconfiguration effect on makespan with social network method for flexible job shop scheduling problem. Computers & Industrial Engineering 110, pages 231-241.
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Yingfeng Zhang, Jin Wang, Sichao Liu & Cheng Qian. (2017) Game Theory Based Real-Time Shop Floor Scheduling Strategy and Method for Cloud Manufacturing. International Journal of Intelligent Systems 32:4, pages 437-463.
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V. K. Manupati, M. Gokula Krishnan, M. L. R. Varela & José Machado. (2017) Telefacturing Based Distributed Manufacturing Environment for Optimal Manufacturing Service by Enhancing the Interoperability in the Hubs. Journal of Engineering 2017, pages 1-15.
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Vijaya Kumar Manupati, Goran D. Putnik, Manoj Kumar Tiwari, Paulo Ávila & Maria Manuela Cruz-Cunha. (2016) Integration of process planning and scheduling using mobile-agent based approach in a networked manufacturing environment. Computers & Industrial Engineering 94, pages 63-73.
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Farayi Musharavati & Abdel Magid S. Hamouda. (2014) Multiple parts process planning in serial–parallel flexible flow lines: part II—solution method based on genetic algorithms with fixed- and variable-length chromosomes. The International Journal of Advanced Manufacturing Technology 77:5-8, pages 1105-1143.
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Fei Tao, Lin Zhang & Yuanjun LailiFei Tao, Yuanjun Laili & Lin Zhang. 2015. Configurable Intelligent Optimization Algorithm. Configurable Intelligent Optimization Algorithm 35 80 .
Vijaya Kumar Manupati, S. N. Dwivedi & Manoj Kumar Tiwari. 2015. Handbook of Manufacturing Engineering and Technology. Handbook of Manufacturing Engineering and Technology 3475 3485 .
V. K. Manupati, S. N. Dwivedi & M. K. Tiwari. 2013. Handbook of Manufacturing Engineering and Technology. Handbook of Manufacturing Engineering and Technology 1 11 .
V.K. Manupati, J.J. Thakkar, K.Y. Wong & M.K. Tiwari. (2013) Near optimal process plan selection for multiple jobs in networked based manufacturing using multi-objective evolutionary algorithms. Computers & Industrial Engineering 66:1, pages 63-76.
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