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We consider the problem of scheduling jobs on parallel identical machines, where only interval bounds of processing times of jobs are known. The optimality criterion of a schedule is the total completion time. In order to cope with the uncertainty, we consider the maximum regret objective and seek a schedule that performs well under all possible instantiations of processing times. We show how to compute...
In this paper new complexity and approximation results on the robust versions of the representatives selection problem, under the scenario uncertainty representation, are provided, which extend the results obtained in the recent papers by Dolgui and Kovalev (2012) and Deineko and Woeginger (2013). Namely, it is shown that if the number of scenarios is a part of input, then the min–max (regret) representatives...
This paper considers two topics in mechanism design: fragility of optimal auctions and computationally constructive procedures for dynamic mechanisms. The first part of the paper considers the well studied topic in mechanism design of optimal auctions, i.e., auctions that produce maximal revenue. The design of an optimal auction in a general setting requires the principal to have complete knowledge...
An elevator group control scheduling (EGCS) method, which is combined with robust optimization (RO) and multi-agents, is proposed to deal with the uncertainty with the elevator traffic flow and the computation complexity. Considering the uncertainty of elevator traffic flow, the elevator schedule model based on RO is developed. An integrated method combined with multi-agent coordination (MAC) and...
A chance-constrained optimization problem, induced from a robust design problem with polynomial dependence on the uncertainties, is, in general, non-convex and difficult to solve. By introducing a novel concept-the kinship function-an easily computable convex relaxation of this problem is proposed. In particular, optimal polynomial kinship functions, which can be computed a priori and once for all,...
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