Abstract
This chapter focuses on the successful collaboration between a research team at the Universidad de La Laguna (Tenerife, Spain) and the firm ITOP Management Consulting, which is a SAP partner mainly interested in developing solutions for SMEs. Company representatives came to our group to propose us both the design of an efficient algorithm to reduce inventory costs in companies, and its eventual integration as an add-on in SAP Business One platform. The problem arises in those firms with storage capacity that should schedule the replenishment orders for several items along a finite planning horizon. After 2 years, the algorithm was finally implemented in C# and .NET. A comprehensive computational experiment was carried out considering a wide range of random instances. The experimental results revealed that heuristic solutions were on average 5 % above the best solution provided by CPLEX optimizer.
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References
Christopher M (2011) Logistics and supply chain management. Pearson Education, Great Britain
Guasch JL, Kogan J (2006) Inventories and logistic costs in developing countries: levels and determinants—A red flag for competitiveness and growth. Revista de la Competencia y de la Propiedad Intelectual. Lima, Perú
Wagner HM, Whitin TM (1958) Dynamic version of the economic lot size model. Manag Sci 5(1):89–96
Veinott AF Jr (1969) Minimum concave-cost solution of leontief substitution models of multifacility inventory systems. Oper Res 7:262–290
Zangwill WI (1966) A deterministic multiproduct multifacility production and inventory model. Oper Res 4:486–507
Love SF (1973) Bounded production and inventory models with piecewise concave costs. Manag Sci 20(3):313–8
Gutiérrez J, Sedeño-Noda A, Colebrook M, Sicilia J (2003) A new characterization for the dynamic lot size problem with bounded inventory. Comput Oper Res 30:383–395
Gutiérrez J, Sedeño-Noda A, Colebrook M, Sicilia J (2007) A polynomial algorithm for the production/ordering planning problem with limited storage. Comput Oper Res 34(4):934–937
Florian M, Lenstra JK, Rinnooy Kan AHG (1980) Deterministic production planning: algorithms and complexity. Manag Sci 26(7):669–679
Minner S (2009) A comparison of simple heuristics for multi-product dynamic demand lot-sizing with limited warehouse capacity. Int J Prod Econ 118:305–310
Dixon PS, Poh CL (1990) Heuristic procedures for multi-item inventory planning with limited storage. IIE Trans 22(2):112–123
Federgruen A, Tzur M (1991) A simple forward algorithm to solve general dynamic lot sizing models with n periods in O(n log n) or O(n) time. Manag Sci 37(8):909–925
Wagelmans A, Hoesel SV, Kolen A (1992) Economic lot sizing: an O(n log n) algorithm that runs in linear time in the Wagner–Whitin case. Oper Res 40(1):145–156
Aggarwal A, Park JK (1993) Improved algorithms for economic lot size problems. Oper Res 41(3):549–571
Günther HO (1991) Bestellmengenplanung aus logistischer sicht. Z Betriebswirtschaft 51:541–555
Axsäter S (1980) Economic lot sizes and vehicles scheduling. Eur J Oper Res 4:395–398
Gutiérrez J, Colebrook M, Abdul-Jalbar B, Sicilia J (2013) Effective replenishment policies for the multi-item dynamic lot-sizing problem with storage capacities. Comput Oper Res 40:2844–2851
Iris C, Yenisey MM (2012) Multi-item simultaneous lot sizing and storage allocation with production and warehouse capacities. In: Hu H, Shi X, Stahlbock R, Voß S (eds) ICCL’12: Third international conference on computational logistics, Shanghai, China, September 2012. Lecture notes in computer science, vol 7555. Springer, Berlin, p 129–141
MVS (2014) MS Visual Studio. http://msdn.microsoft.com/en-us/vstudio/aa718325. Accessed 1 Sep 2014
SAP BO SDK (2014) SAP Business One SDK General. http://scn.sap.com/docs/DOC-28739. Accessed 1 Sep 2014
Acknowledgments
This work is partly supported by the former Spanish Ministry of Science and Innovation through the Research Project with reference MTM2010-18591 and by the new Spanish Ministry of Economy and Competitiveness through the Research Project with reference MTM2013-43396-P.
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Gutiérrez, J.M., Colebrook, M., Rivero, C., Pestana, T. (2015). Integration of a Heuristic Method into an ERP Software: A Successful Experience for a Dynamic Multi-item Lot Sizing Problem. In: García Márquez, F., Lev, B. (eds) Advanced Business Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-11415-6_2
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DOI: https://doi.org/10.1007/978-3-319-11415-6_2
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