This paper develops the team-building models under uncertainty of agents abilities described by Pareto distribution, and is organized as follows. At first, some properties of Pareto distribution required for further presentation are briefly discussed in Section 2. Then the solution of the team incentive problem is given in Section 3. Section 4 presents the team-building problem statement. Secti...

Data envelopment analysis (DEA) measures relative efficiency among the decision making units (DMU) without considering noise in data. The least efficient DMU indicates that it is in the worst situation. In this paper, we measure efficiency of individual DMU whenever it losses the maximum output, and the efficiency of other DMUs is measured in the observed situation. This efficiency is the minim...

The carbon emission of China’s industry accounts for more than 70% of the total in the nation, thus the implementation of carbon emission quota trading in industry is of great importance to realize China’s national carbon emission reduction targets. Meanwhile, the allocation of carbon emission quota among sectors or enterprises proves the first and critical step. For this reason, this paper con...

Most methods for finding interesting gene expression profiles from gene microarray data are based on a single discriminant, e.g. the classical paired t-test. Here a different approach is introduced based on gene ranking according to Pareto depth in multiple discriminants. The novelty of our approach, which is an extension of our previous work on Pareto front analysis (PFA), is that a gene’s rel...

A new game theoretical solution concept for open spectrum sharing in cognitive radio (CR) environments is presented – the Lorenz equilibrium (LE). Both Nash and Pareto solution concepts have limitations when applied to real world problems. Nash equilibrium (NE) rarely ensures maximal payoff and it is frequently Pareto inefficient. The Pareto set is usually a large set of solutions, often too ha...

In this paper we present results from analytical and experimental investigations into the performance of divide & conquer algorithms for determining Pareto points in multidimensional data sets of size n and dimension d. The focus in this work is on the worst-case, where all points are Pareto, but extends to problem sets where only a partial subset of the points is Pareto. Analysis supported by ...

In this study, biobjective mixed-integer linear programming problems are considered and a search-andremove (SR) algorithm is presented. At each stage of the algorithm, Pareto outcomes are searched with the dichotomic search algorithm and these outcomes are excluded from the objective space with the help of Tabu constraints. The algorithm is also enhanced with lower and upper bounds, which are u...