A new game theoretical solution concept for open spectrum sharing in cognitive radio (CR) environments is highlighted – 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 ...

This paper proposes a practical methodology for the solution of multi-objective system reliability optimization problems. The new method is based on the sequential combination of multi-objective evolutionary algorithms and data clustering on the prospective solutions to yield a smaller, more manageable sets of prospective solutions. Existing methods for multiple objective problems involve eithe...

Selecting a set of alternatives based on the preferences of agents is an important problem in committee selection and beyond. Among the various criteria put forth for desirability of a committee, Pareto optimality is a minimal and important requirement. As asking agents to specify their preferences over exponentially many subsets of alternatives is practically infeasible, we assume that each ag...

Pareto Local Search (PLS) is a generalization of the local search algorithms to handle more than one objective. In this paper, two variants of PLS are examined on the multiobjective 0/1 knapsack problems, compared with three well-known multiobjective EA algorithms, namely SPEA, SPEA2 and NSGA2. Furthermore, A Guided Local Search (GLS) based multiobjective optimization algorithm is proposed, the...

Selecting a set of alternatives based on the preferences of agents is an important problem in committee selection and beyond. Among the various criteria put forth for the desirability of a committee, Pareto optimality is a minimal and important requirement. As asking agents to specify their preferences over exponentially many subsets of alternatives is practically infeasible, we assume that eac...

This paper is concerned with the problem of finding a representative sample of Pareto-optimal points inmulti-objective optimization. The Normal Boundary Intersection algorithm is a scalarization scheme for generating a set of evenly spaced Efficient solutions. A drawback of this algorithm is that Pareto-optimality of solutions is not guaranteed. The contributions of this paper are two-fold. Fir...

A new multiobjective selection procedure for Genetic Algorithms based on the paradigms of fuzzy logic is discussed and compared to the niched Pareto selection procedure. In the example presented here the fuzzy logic procedure optimized the parameters of a series of functions in a more efficient manner than the niched Pareto approach. The main advantage that the fuzzy logic approach has over the...

In this paper we introduce and study enhanced notions of relative Pareto minimizers to constrained multiobjective problems that are defined via several kinds of relative interiors of ordering cones and occupy intermediate positions between the classical notions of Pareto and weak Pareto efficiency/minimality. Using advanced tools of variational analysis and generalized differentiation, we estab...