Classification of Supply Network Optimization Models

Categorization schemes have been suggested both for facility location (e.g., Hamacher and Nickel 1998 Ballou 1992, pp. 323-324 Brandeau and Chiu 1989, pp. 647-650) and supply chain optimization models (e.g., Bankhofer 2003, pp. 27-34 Bestmann 2001, pp. 46-47) and many literature reviews contain classifications of the models they review. The following criteria (the abbreviations in brackets are used in Table 4), extending the classification introduced by Melo et al. (2005, p. 198), are used to classify the models from literature contained in Table 4  

24 Often, models are characterized as being static or dynamic having the same distinction in mind. This terminology can however be confused with dynamic programming and is therefore not used here. 

25 Some authors further distinguish between decision-making under uncertainty and decision-making under risk with the former referring to a situation where no quantitative information on the uncertain parameters is available and the latter referring to a situation where a well-determined probability distribution is available (cf. Wets 1974, pp. 309-310). Here, this distinction will not be used. 

26 Production network design by definition needs to include distribution decisions. For the purpose of this classification a model is considered to include distribution network design only if at least one distribution echelon (warehouses, distribution centers, etc.) is explicitly modeled. The term distribution center is not defined uniformly in literature (cf. Higginson and Bookbinder 2005). Here, distribution centers where a production step takes place are considered to be a production echelon whereas those performing picking or packaging operations are considered to be a distribution echelon. 

A Automotive industry C Chemical industry E Electronics industry F Food processing P Pulp and Paper industry S Steel industry 

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Table 4. Classification of supply network optimization models...

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