Friedrich, Hanno and Jonathan Gumpp

Simplified Modeling and Solving of Logistics Optimization Problems

International Journal of Transportation, 2 (1): 52-33, (2014).

Copy reference link   DOI: 10.14257/ijt.2014.2.1.03

Abstract: Logistics optimization problems are often complex (NP - hard). Especially for large problem scopes in logistics and new agent-based freight transport models which have to solve these problems for many agents, simplifying modelling and solving procedures are necessary in order to reduce the level of complexity. Due to the variety of existing approaches and the specifics of each problem it is often difficult to find an appropriate method. This paper seeks to facilitate this process as it identifies ‘meta’ heuristics within literature, i.e. abstract courses of action that, when adapted, have proven successful in various problems. It presents a classification of general simplification principles that are useful for reducing the complexity of logistics problems, in order to facilitate understanding between academics and practice. The derivation of the related principles is based on the examination of five problems in logistics literature: facility location, distribution system, lot size, bin packing, and vehicle routing.

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