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Concave Cost Supply Management for Single Manufacturing Unit

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Supply Chain Optimisation

Part of the book series: Applied Optimization ((APOP,volume 94))

Abstract

The considered problem consists of product delivery from a set of providers to the manufacturing units (single unit and single planning period in our case). The cost function is concave. Given the lower and upper bounds on the shipment size for each provider, the demand of the manufacturing unit has to be satisfied. In this chapter it is shown that this optimisation problem is NP-hard even to find a feasible solution to this problem. Considering the problem in integer programming formulation we propose a pseudo-polynomial algorithm, using the dynamic programming technique. Some possible approaches to solving the problem with multiple manufacturing units are discussed.

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References

  1. Bakhtin A.E., Kolokolov A.A. and Korobkova Z.B., 1978. Discrete Problems of Production-Transportation Type, Nauka, Novosibirsk. (in Russian).

    Google Scholar 

  2. Chauhan S.S. and Proth J.-M., 2003. The concave cost supply problem. European Journal of Operational Research, 148(2), 374–383.

    Article  MathSciNet  Google Scholar 

  3. Garey M.R. and Johnson D.S., 1979. Computers and Intractability. A Guide to the Theory of NP-Completeness, W.H. Freeman and Company, San Francisco.

    Google Scholar 

  4. Hu T.C., 1970. Integer Programming and Network Flows, Addison-Wesley Pbl.

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  5. Kolokolov A.A., 1994. Decomposition algorithms for solving of some production-transportation problems. In: Preprints of Triennial Symposium on Transportation Analysis II., Vol. 1, Capri, Italy, 179–183.

    MathSciNet  Google Scholar 

  6. Kolokolov A.A. and Levanova T.V., 1996. Decomposition and L-class enumeration algorithms for solving some location problems. Vestnik Omskogo Universiteta, 1, Omsk, OmSU, 21–23. (in Russian).

    Google Scholar 

  7. Schrijver A., 1986. Theory of Linear and Integer Programming, John Wiley Sons, Vol. 2.

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  8. Yan S. and Luo S.-C., 1999. Probabilistic local search algorithms for concave cost transportation network problems. European Journal of Operational Research, 117, 511–521.

    Article  Google Scholar 

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© 2005 Springer Science + Business Media, Inc.

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Chauhan, S.S., Eremeev, A., Kolokolov, A., Servakh, V. (2005). Concave Cost Supply Management for Single Manufacturing Unit. In: Dolgui, A., Soldek, J., Zaikin, O. (eds) Supply Chain Optimisation. Applied Optimization, vol 94. Springer, Boston, MA. https://doi.org/10.1007/0-387-23581-7_12

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