id: 06105880
dt: a
an: 06105880
au: Zhang, Yingqian; Verwer, Sicco
ti: Mechanism for robust procurements.
so: Rahwan, Iyad (ed.) et al., PRIMA 2012: Principles and practice of
    multi-agent systems. 15th international conference, Kuching, Sarawak,
    Malaysia, September 3‒7, 2012. Proceedings. Berlin: Springer (ISBN
    978-3-642-32728-5/pbk). Lecture Notes in Computer Science 7455. Lecture
    Notes in Artificial Intelligence, 77-91 (2012).
py: 2012
pu: Berlin: Springer
la: EN
cc: 
ut: 
ci: 
li: doi:10.1007/978-3-642-32729-2_6
ab: Summary: We model robust procurement as an optimization problem. We show
    that its decision version is NP-complete, and propose a backtracking
    algorithm with cuts that reduce the search-space to find the optimal
    solution. We then develop a mechanism that motivates agents to
    truthfully report their private information (i.e., truthful in dominant
    strategies), maximizes the social welfare (efficient), and ensures
    non-negative utilities of the participating agents even after execution
    (post-execution individually rational). In the experiments, we compare
    our mechanism with an iterated greedy first-price mechanism that
    represents the current practice in public procurements, in terms of the
    expected social welfare and the expected payments of the auctioneer.
    The results show that in terms of social welfare, our mechanism
    outperforms the greedy approach in all cases except when there exist
    cheap and reliable agents who can finish the job in time. In terms of
    payments, our mechanism outperforms the current practice when there are
    many potential contractors and the optimization constraints are tight.
rv: