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Application of traveling salesman problem (TSP) for decision of optimal production sequence

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Abstract

In the present study a reliable and structural decision system for production sequence of polymeric products is developed. Minimization of the amount of off-specs is the main objective in the decision of production sequence to maximize profit. Off-specs are generated when the production sequence of polymeric products is changed. The amount of off-specs depends on changes of product grades. In the present study we applied the traveling salesman problem (TSP) to achieve optimal decision of production sequence. To solve the optimal decision problem formulated by TSP, we employed three different approaches such as Branch and Bound (B&B) method, Dynamic Programming (DP) method and Hopfield Neural Network (HNN) method. Production sequences computed based on the actual plant off-spec data were compared with the sequences employed in the actual plant operation. From the comparison the decision method proposed in the present study showed increased profits and reduced off-specs.

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References

  • Cichocki, A. and Unbehauen, R., “Neural Network for Optimization and Signal Processing”, John Wiley & Sons Ltd. & B. G. Teubner, Stuttgart, New York, 1993.

    Google Scholar 

  • Egbelu, P. J. and Lehtihet, A., “Operation Routing with Lot Sizing Consideration in a Manufacturing System”,Int. J. Production Research,28(3), 503 (1990).

    Article  Google Scholar 

  • Elsayed, A. E. and Boucher, T. O., “Analysis and Control of Production System”, Prentice-Hall Inc., Englewood Cliffs, New Jersey, 1994.

    Google Scholar 

  • Fausett, L., “Fundamentals of Neural Networks-Architecture, Algorithm, and Applications”, Prentice-Hall Inc., Englewood Cliffs, New Jersey, 1994.

    Google Scholar 

  • Ignzio, J. P. and Cavalier, T. M., “Linear Programming”, Prentice-Hall, Englewood Cliffs, New Jersey, 1994.

    Google Scholar 

  • Lawler, E. L. and Wood, D. E., “Branch-and-Bound Method: A Survey”,Operation Research,11, 699 (1966).

    Google Scholar 

  • Little, John D. C., Murty, K. G., Sweeney, D. W. and Karel, C., “An Algorithm for the Traveling Salesman Problem”,Operation Research,11(6), 972 (1963).

    Article  Google Scholar 

  • Murty, K. G., “Operation Research Deterministic Optimization Models”, Prentice-Hall, Englewood Cliffs, New Jersey, 1995.

    Google Scholar 

  • Padberg, M. and Rinaldi, G., “A Branch-and-Cut Approach to a Traveling Salesman Problem with Side Constraints”,Institute of Management Sciences,35(11), (1989).

  • Zurada, J. M., “Introduction to Artificial Neural Systems”, into Access & Distribution Ptd Ltd., Singapore 1992.

    Google Scholar 

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Jeong, EY., Oh, S.C., Yeo, YK. et al. Application of traveling salesman problem (TSP) for decision of optimal production sequence. Korean J. Chem. Eng. 14, 416–421 (1997). https://doi.org/10.1007/BF02707062

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  • DOI: https://doi.org/10.1007/BF02707062

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