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Original Articles

Improving the design of stochastic production lines: an approach using perturbation analysis

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Pages 2789-2806 | Received 01 May 1992, Published online: 27 Apr 2007

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Khelil Kassoul, Naoufel Cheikhrouhou & Nicolas Zufferey. (2024) Simultaneous allocation of buffer capacities and service times in unreliable production lines. International Journal of Production Research 62:3, pages 644-664.
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Xiaolan Xie, Sophie Hennequin & Iyad Mourani. (2013) Perturbation analysis and optimisation of continuous flow transfer lines with delay. International Journal of Production Research 51:23-24, pages 7250-7269.
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EYLEM TEKIN & IHSAN SABUNCUOGLU. (2004) Simulation optimization: A comprehensive review on theory and applications. IIE Transactions 36:11, pages 1067-1081.
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Articles from other publishers (8)

Edwards A. Silver, David F. Pyke & Douglas J. Thomas. 2016. Inventory and Production Management in Supply Chains. Inventory and Production Management in Supply Chains 661 712 .
Erinc Albey & Reha Uzsoy. (2015) Lead time modeling in production planning. Lead time modeling in production planning.
Long-Fei WANG & Le-Yuan SHI. (2013) Simulation Optimization: A Review on Theory and Applications. Acta Automatica Sinica 39:11, pages 1957-1968.
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Ding-zhong Feng, Mei-xian Jiang & Lei-lei Chen. (2005) Lead-time planning in stochastic production system: an approach using perturbation analysis. Lead-time planning in stochastic production system: an approach using perturbation analysis.
D.J Wu. (2001) Software agents for knowledge management: coordination in multi-agent supply chains and auctions. Expert Systems with Applications 20:1, pages 51-64.
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D. J. Wu. (2000) Agent-based stochastic production lines design. International Journal of Intelligent Systems in Accounting, Finance & Management 9:4, pages 257-270.
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D.-J. Wu. (2000) Shop floor production community design: artificial agents based approach. Shop floor production community design: artificial agents based approach.
David M. Steiger & Ramesh Sharda. (1996) Analyzing mathematical models with inductive learning networks. European Journal of Operational Research 93:2, pages 387-401.
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