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A stochastic programming approach to determine robust delivery profiles in area forwarding inbound logistics networks

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Abstract

One technique to coordinate the suppliers’ and the producers’ production plans in a supply chain is the use of delivery profiles, which provide fixed delivery frequencies for all suppliers. The selection of a delivery profile assignment has major effects on the cost efficiency and the robustness of a supply chain and thus should be performed carefully. In this work, we consider planning approaches to select delivery profiles for the case of area forwarding-based inbound logistics networks, which are commonly used in several industries to consolidate supplies in an early stage of transport. We present a two-stage stochastic mixed integer linear programming model to determine robust delivery profile assignments under uncertain and infrequent demands and complex tariff systems. The model is embedded into a solution framework consisting of scenario generation and reduction techniques, a decomposition approach, a genetic algorithm, and a standard MILP solver. On the basis of an industrial case study, we show that our approach is computationally feasible and that the planning solutions obtained by our model outperform both a deterministic approach and the planning methodology prevailing in industrial practice.

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Authors and Affiliations

  1. Universität Paderborn, Warburger Str. 100, 33098 , Paderborn, Germany

    Tim Schöneberg & Leena Suhl

  2. Goethe Universität Frankfurt, Grüneburgplatz 1, 60323 , Frankfurt am Main, Germany

    Achim Koberstein

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  1. Tim Schöneberg
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  2. Achim Koberstein
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  3. Leena Suhl
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Correspondence to Achim Koberstein.

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Schöneberg, T., Koberstein, A. & Suhl, L. A stochastic programming approach to determine robust delivery profiles in area forwarding inbound logistics networks. OR Spectrum 35, 807–834 (2013). https://doi.org/10.1007/s00291-013-0349-0

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