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Algorithm for the stochastic generalized transportation problem

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  • Marcin Anholcer

Abstract

The equalization method for the stochastic generalized transportation problem has been presented. The algorithm allows us to find the optimal solution to the problem of minimizing the expected total cost in the generalized transportation problem with random demand. After a short introduction and literature review, the algorithm is presented. It is a version of the method proposed by the author for the nonlinear generalized transportation problem. It is shown that this version of the method generates a sequence of solutions convergent to the KKT point. This guarantees the global optimality of the obtained solution, as the expected cost functions are convex and twice differentiable. The computational experiments performed for test problems of reasonable size show that the method is fast.

Suggested Citation

  • Marcin Anholcer, 2012. "Algorithm for the stochastic generalized transportation problem," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 22(4), pages 9-20.
  • Handle: RePEc:wut:journl:v:4:y:2012:p:9-20:id:1025
    DOI: 10.5277/ord120401
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    References listed on IDEAS

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    1. Liqun Qi, 1987. "The A -Forest Iteration Method for the Stochastic Generalized Transportation Problem," Mathematics of Operations Research, INFORMS, vol. 12(1), pages 1-21, February.
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    7. Kevin D. Wayne, 2002. "A Polynomial Combinatorial Algorithm for Generalized Minimum Cost Flow," Mathematics of Operations Research, INFORMS, vol. 27(3), pages 445-459, August.
    8. Andrew V. Goldberg & Serge A. Plotkin & Éva Tardos, 1991. "Combinatorial Algorithms for the Generalized Circulation Problem," Mathematics of Operations Research, INFORMS, vol. 16(2), pages 351-381, May.
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    Cited by:

    1. Marcin Anholcer, 2013. "Stochastic Generalized Transportation Problem with discrete distribution of demand," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 23(4), pages 9-19.

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