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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@inproceedings{Leaute11,
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 =
{http://thomas.leaute.name/main/privacy_logistics_ijcai11.html},
Year =
{2011}
}