We introduce and study a family of models for multi-expert multi-objective/criteria decision making. These models use a concept of weight robustness to generate a risk averse decision. In particular, the multi-expert multi-criteria robust weighted sum approach (McRow) introduced in this paper identifies a (robust) Pareto optimum decision that minimizes the worst case weighted sum of objectives ...

Multi-modal multi-objective optimization problems (MMMOPs) have multiple subsets within the Pareto-optimal Set, each independently mapping to same Pareto-Front. Prevalent evolutionary algorithms are not purely designed search for solution subsets, whereas, MMMOPs demonstrate degraded performance in objective space. This motivates design of better addressing MMMOPs. The present work identifies c...

data envelopment analysis (dea) is a managerial powerful tool for assess the performance of decision making units (dmus). nowadays, multi-objective dea models are an attractive technique for evaluation quantity and quality aspects of performance analysis. but these models are in static. in this paper, we want to present a proposed fuzzy dynamic multi-objective dea model in which data are changi...

Most of data in a multi-attribute decision making (MADM) problem are unstable and changeable, then sensitivity analysis after problem solving can effectively contribute to making accurate decisions. This paper provides a new method for sensitivity analysis of MADM problems so that by using it and changing the weights of attributes, one can determine changes in the final results of a decision ma...