Integer and combinatorial optimization
Integer and combinatorial optimization
A continuous approach to the design of physical distribution systems
Computers and Operations Research
HubLocator: an exact solution method for the multiple allocation hub location problem
Computers and Operations Research - Location analysis
Heuristic Methods for Large Centroid Clustering Problems
Journal of Heuristics
Location models for airline hubs behaving as M/D/c queues
Computers and Operations Research
A Joint Location-Inventory Model
Transportation Science
Analysis of cost of performing communications using various communication mechanisms
FRONTIERS '95 Proceedings of the Fifth Symposium on the Frontiers of Massively Parallel Computation (Frontiers'95)
On the Stability of Supply Chains
Operations Research
Designing And Managing The Supply Chain
Designing And Managing The Supply Chain
Solution approaches for facility location of medical supplies for large-scale emergencies
Computers and Industrial Engineering
Game theoretical applications for multi-agent systems
Expert Systems with Applications: An International Journal
A hierarchical optimization technique for the strategic design of distribution networks
Computers and Industrial Engineering
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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.