The talk focuses on the simultaneous resource allocation, lot-sizing and scheduling in a multi-machine, deterministic ELSP environment. The objective is to minimize the long-run average production, setup, inventory, and shortage penalty costs. We develop a concave minimization model of the problem, generate heuristic solutions, lower bounding methods and present computational results.

 Ambiguity in the inputs of the models is typical especially in portfolio selection problem where the true distribution of random variables is usually unknown. Here we use robust optimization approach to address the ambiguity in conditional-value-at-risk minimization model. We obtain explicit models of the robust conditional-value-at-risk minimization for polyhedral and correlated polyhedral am...

The consistency of classification algorithm plays a central role in statistical learning theory. A consistent algorithm guarantees us that taking more samples essentially suffices to roughly reconstruct the unknown distribution. We consider the consistency of ERM scheme over classes of combinations of very simple rules (base classifiers) in multiclass classification. Our approach is, under some...

In low order-value optimization (LOVO) problems the sum of the r smallest values of a finite sequence of q functions is involved as the objective to be minimized or as a constraint. The latter case is considered in the present paper. Portfolio optimization problems with a constraint on the admissible Value-at-Risk (VaR) can be modeled in terms of LOVOconstrained minimization. Different algorith...