Dominance measuring methods are a recent approach for dealing with complex decisionmaking problems with imprecise, incomplete or partial information within multi-attribute value/utility theory. These methods compute pairwise dominance values and exploit the information included in the dominance matrix in different ways to derive measures of dominance intensity to rank the alternatives under con...

In this study, 76 men came into the lab in pairs and engaged in a 7-minute videotaped mate competition for the attention of an attractive female confederate. Pre-competition testosterone (T) levels were positively associated with men’s dominance behaviors and with how much the confederate indicated that she ‘‘clicked’’ with each participant. Dyadic analyses showed that self-reported dominance m...

We establish for the first time a formal relationship between dominance graphs, used for modeling semantics, and grammar formalisms with underspecified dominance links, used for modeling syntax. We present a translation of normal dominance graphs into Unordered Vector Grammars with Dominance Links (UVG-DL) and prove that the configurations of the dominance graph correspond to the derivation tre...

the set covering problem (scp) is a well-known combinatorial optimization problem. this paper investigates development of a local branching approach for the scp. this solution strategy is exact in nature, though it is designed to improve the heuristic behavior of the mixed integer programming solver. the algorithm parameters are tuned by design of experiments approach. the proposed method is te...

in structural time seriesregression models, binary (classic) dummy variables are used to quantify the effects of economic structural breaks, changes or qualitative variables. the binary dummy variable can be challenged using this dummy variable in which 0 or 1 represent absence or presence of structural breaks(or changes), but presence of the structural breaks(or changes) may not have uniform e...

In order to discover interesting patterns and dependencies in data, an approach based on rough set theory can be used. In particular, Dominance-based Rough Set Approach (DRSA) has been introduced to deal with the problem of ordinal classification with monotonicity constraints (also referred to as multicriteria classification in decision analysis). However, in real-life problems, in the presence...

The rough set theory was proved of its effectiveness in dealing with the imprecise and ambiguous information. Dominance-based Rough Set Approach (DRSA), as one of the extensions, is effective and fundamentally important for Multiple Criteria Decision Analysis (MCDA). However, most of existing DRSA models cannot directly examine uncertain information within rough boundary regions, which might mi...

Soft computing offers a large variety of tools for decision making. This special issue focuses on different aspects related to soft computing and its application to decision problems. Papers were selected among the ones presented at the 5th Interantional Conference on Modeling Decisions for Artificial Intelligence (MDAI 2008) celebrated in Sabadell (Catalonia, Spain). Eight of the papers includ...

In the paper, we present a new interval-based set inversion algorithm which takes into account continuity of problem. case where Y to be inverted has some volume, show that inverting boundary ∂Y is sufficient reconstruct preimage X=f−1(Y). The separates domain f two regions : one inside X and outside. To detect part or outside, can retro-propagate information coming from at negligible cost. eff...