e-Work based collaborative optimization approach for strategic logistic network design problem

Pablo A. Miranda

doi:10.1016/j.cie.2008.12.007

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e-Work based collaborative optimization approach for strategic logistic network design problem

2009-08-01

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Pablo A. Miranda

Rodrigo A. Garrido

José Ceroni *

DOI：10.1016/j.cie.2008.12.007

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Abstract

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We propose a collaborative e-Work based optimization approach for assisting the strategic logistic network design problem, which considers fleet design and customer clustering decisions. Normally, fleet design and customer clustering decisions are made by mid-level logistics managers while network design decision is made independently by high-level logistics managers. In the proposed approach, strategic distribution network design is modeled as a Facility Location Problem, considering long term inventory control decisions. On the other hand, tactical fleet design and customer clustering decisions are modeled based on a Hub and Spoke cost structure. An e-Work based heuristic approach is proposed to solve collaboratively the network design problem at strategic and tactical levels. The collaborative solution approach results from a particular sequential decomposition of the problem, similarly to traditional location-allocation heuristics, modeling an information sharing strategy between decision makers involved at each organizational level. A numerical application of the approach with real data based instances shows significant benefits, when compared to a non-collaborative independent optimization, where the hierarchical levels share no dynamic information and base their decisions on static and independent optimization models. These results show evidence of the advantage of the e-collaborative approach to deal with logistic decisions at different hierarchical levels, organizational units, or companies, compared to non-integrated non-linear mixed integer programming models. (c) 2008 Elsevier Ltd. All rights reserved.

Keywords:

e-Work

Collaborative optimization

Logistic distribution network design

Inventory location problem

Fleet design

Customer clustering

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