SCOptimizer — A Prototype for Quantifying Benefits of Cooperative Planning in Supply Chains



Supply Chain Bullwhip Effect Capacitate Vehicle Route Problem Transportation Capacity Cooperative Scenario 
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  1. 107.
    This prototypical implementation is an auxiliary means of research as described by König (1994) in his paper on the profile of “Wirtschaftsinformatik” (the German “Wirtschaftsinformatik” can be understood as the counterpart of the Anglo-Saxon “Information Systems” research field).Google Scholar
  2. 109.
    For a comprehensive introduction and overview to vehicle routing and scheduling problems refer to Domschke (1997, pp. 204ff).Google Scholar
  3. 110.
    For a detailed am overview on transportation costs characteristics refer for example to Ballou (1999, pp. 153ff) or Bowersox and Closs (1996, pp. 368ff).Google Scholar
  4. 112.
    Chen et al. (2000, p. 437) point out that the calculation of the reorder point is based on the standard deviation of the forecasting error σeL whose estimator is \( \hat \sigma _{et}^L \) and not based on the standard deviation of the demand in the lead time σL whose estimator is \( \hat \sigma _t^L \) . Although there is a simple relationship between both terms (σeL = L, with c being a constant c≥ 1), it is still appropriate to use \( \hat \sigma _{et}^L \) (refer to Hax & Candea, 1984, p. 194, for the proof).Google Scholar
  5. 113.
    Chen et al. (2000) refer to the proove presented in Ryan (1997) and Chen et al. (1998).Google Scholar

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© Deutscher Universitäts-Verlag ∣ GWV Fachverlage GmbH, Wiesbaden 2006

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