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Information Technology Journal

Year: 2013 | Volume: 12 | Issue: 20 | Page No.: 5799-5805
DOI: 10.3923/itj.2013.5799.5805
Schedule of a Resource-constraint Manufacturing System Based on GA
Wang Yuxia

Abstract: The purpose of this study is to verify a schedule mechanism based on Theory of constraint for a Resource-constraint Manufacturing System while in face of peak demand in certain period for the whole system, the system would achieve a holistic profitability. A numerical example has been adopted to demonstrate the efficiency of the proposed schedule mechanism based on TOC and as the processing procedure is a typical target allocation problem, genetic algorithm was used in the computation. The proposed mechanism based on TOC is far more efficient compared with the formal mechanism based on the quantity of the order.

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How to cite this article
Wang Yuxia , 2013. Schedule of a Resource-constraint Manufacturing System Based on GA. Information Technology Journal, 12: 5799-5805.

Keywords: Capacity allocation, genetic algorithm and theory of constraints

REFERENCES
  • Blackstone, J.H., 2001. Theory of Constraints-a status report. Int. J. Prod. Res., 6: 1053-1080.
    CrossRef    

  • Belvedere, V. and A. Grando, 2005. Implementing a pull system in batch/mix process industry through theory of constraints: A Case-study. Human Syst. Manage., 24: 3-12.
    Direct Link    

  • Bhattacharya, A. and P. Vasant, 2007. Soft-sensing of level of satisfaction in TOC product-mix decision heuristic using robust fuzzy-LP. Eur. J. Operat. Res., 177: 55-70.
    CrossRef    

  • Cole, H. and D. Jacob, 2002. Introduction to TOC supply chain. AGI Institute, 2002.

  • Troxler, J.W. and L. Blank, 1989. A comprehensive methodology for manufacturing system evaluation and comparison. J. Manuf. Syst., 8: 175-183.
    CrossRef    

  • Leng, K. and X. Chen, 2012. A genetic algorithm approach for TOC-based supply chain coordination. Applied Math. Inform. Sci., 6: 767-774.
    Direct Link    

  • Lee, Y.H., C.S. Jeong and C. Moon, 2002. Advanced planning and scheduling with outsourcing in manufacturing supply chain. Comput. Ind. Eng., 43: 351-374.
    CrossRef    

  • Luebbe, R. and B. Finch, 1992. Theory of constraints and linear programming: A comparison. Int. J. Prod. Res., 30: 1471-1478.
    CrossRef    

  • Naso, D., M. Surico, B. Turchiano and U. Kaymak, 2007. Genetic algorithms for Supply-chain scheduling: A case study in the distribution of Ready-mixed concrete. Eur. J. Operat. Res., 177: 2069-2099.
    CrossRef    

  • Primrose, P.L. and R. Leonard, 1991. Selecting technology for investment in flexible manufacturing. Int. J. Flexible Manuf. Syst., 4: 51-77.
    CrossRef    

  • Simatupang, T.M., A.C. Wright and N. Sridharan, 2004. Applying the theory of constraints to manufacturing system collaboration. Manuf. Syst. Manage.: Int. J., 1: 57-70.

  • Torabi, S.A., S.M.T. Fatemi Ghomi and B. Karimi, 2006. A hybrid genetic algorithm for the finite horizon economic lot and delivery scheduling in supply chains. Eur. J. Operat. Res., 173: 173-189.
    CrossRef    

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