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The problem of averaging outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The so-called Weighted OWA (WOWA) aggregation offers a well-suited approach to this problem. The WOWA aggregation, similar to the classical ordered weighted averaging (OWA), uses the preferential(More)
The problem of aggregating multiple criteria to form overall objective functions is of considerable importance in many disciplines. The most commonly used aggregation is based on the weighted sum. The ordered weighted averaging (OWA) aggregation, introduced by Yager, uses the weights assigned to the ordered values (i.e. to the worst value, the second worst(More)
The problem of aggregating multiple numerical criteria to form overall objective functions is of considerable importance in many disciplines. The ordered weighted averaging (OWA) aggregation, introduced by Yager, uses the weights assigned to the ordered values rather than to the specific criteria. This allows one to model various aggregation preferences,(More)
XRCC2 and XRCC3 proteins are structurally and functionally related to RAD51 which play an important role in the homologous recombination, the process frequently involved in cancer transformation. In our previous work we show that the 135G>C polymorphism (rs1801320) of the RAD51 gene can modify the effect of the Thr241Met polymorphism (rs861539) of the XRCC3(More)
The problem of averaging outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The fuzzy operator defined as the so-called Weighted OWA (WOWA) aggregation offers a well-suited approach to this problem. The WOWA aggregation, similar to the classical ordered weighted averaging(More)
The approach called the Lexicographic Min-Max (LMM) optimization depends on searching for solutions minimal according to the lex-max order on a multidimensional outcome space. LMM is a refinement of the standard Min-Max optimization, but in the former, in addition to the largest outcome, we minimize also the second largest outcome (provided that the largest(More)
—The problem of fair resource allocation is of considerable importance in many applications. In this paper advanced aggregation operators based on the Ordered Weighted Averaging (OWA) are utilized as consistent and fairness–preserving approach to modeling various preferences with regard to distribution of Internet traffic between network participants. The(More)
—Allocating bandwidth to maximize service flows with fair treatment of all the services is a key issue in network dimensioning. In such applications, the so-called Max-Min Fairness (MMF) solution concept is widely used. It is based on the worst service performance maximization with additional regularization by the lexicographic maximization of the second(More)
This note is focused on computational efficiency of the portfolio selection models based on the Conditional Value at Risk (CVaR) risk measure. The CVaR measure represents the mean shortfall at a specified confidence level and its optimization may be expressed with a Linear Programming (LP) model. The corresponding portfolio selection models can be solved(More)