nowadays, the necessity of accurate quantitative decision support methods is becoming a critical subject for managers as rivalry between organizations caused a more fragile economic environment and brand reputation is becoming more important. furthermore, dealing with incidents after they happened is not accepted by customers anymore. managers require powerful decision making tools to support t...

in traditional portfolio selection model coefficients often are certain and deterministic, but in real world these coefficients are probabilistic. so decision maker cannot estimate them exactly. financial optimization is one of the most attractive areas in decision under uncertainty. in the portfolio selection problem the decision maker considers simultaneously conflicting objectives such as ra...

We propose a general framework for support vector machines (SVM) based on the principle of multi-objective optimization. The learning of SVMs is formulated as a multiobjective program by setting two competing goals to minimize the empirical risk and minimize the model capacity. Distinct approaches to solving the MOP introduce various SVM formulations. The proposed framework enables a more effec...

The convexity theory plays an important role in many aspects of mathematical programming. In recent years, in order to relax convexity assumption, various generalized convexity notions have been obtained. One of them is the concept of ) , ( r p B− invexity defined by T.Antczak [1], which extended the class of B − invex functions with respect toη and b and the classes of ) , ( r p invex function...