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Coordinating Logistics Operations with Privacy Guarantees

Thomas Léauté, Boi Faltings

Published in Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI'11), 2011


Several logistics service providers serve a certain number of customers, geographically spread over an area of operations. They would like to coordinate their operations so as to minimize overall cost. At the same time, they would like to keep information about their costs, constraints and preferences private, thus precluding conventional negotiation. We show how AI techniques, in particular Distributed Constraint Optimization (DCOP), can be integrated with cryptographic techniques to allow such coordination without revealing agents' private information. The problem of assigning customers to companies is formulated as a DCOP, for which we propose two novel, privacy-preserving algorithms. We compare their performances and privacy properties on a set of Vehicle Routing Problem benchmarks.

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    Address = {Barcelona, Spain},
    Author = {Thomas L{\'e}aut{\'e} and Boi Faltings},
    Booktitle = {Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI'11)},
    Month = {July~16--22},
    Pages = {2482--2487},
    Title = {Coordinating Logistics Operations with Privacy Guarantees},
    Url = {},
    Year = {2011}