We investigate the domain of comprehensive but not necessarily convex bargaining problems. Without convexity the Nash solution is not well de ̄ned. We propose a new solution, the Nash Extension, that coincides with the Nash solution when S is convex. We characterize it by Weak Pareto Optimality, Symmetry, Scale Invariance, Continuity, and a new axiom, Ethical Monotonicity. Journal of Economic Li...

Combining ideas from evolutionary algorithms, decomposition approaches and Pareto local search, this paper suggests a simple yet efficient memetic algorithm for combinatorial multiobjective optimization problems: MoMad. It decomposes a combinatorial multiobjective problem into a number of single objective optimization problems using an aggregation method. MoMad evolves three populations: popula...

The problems presented and analyzed in this paper are interesting testproblems for multi-objective optimization. The aim is to find the distance to two points in a d-dimensional space. Closed analytical expressions of all pareto-optimal fronts and pareto-optimal sets will be derived in this paper. Moreover, a discussion of the characteristics of the properties of these sets is given. Depending ...

This paper addresses a general multiobjective optimization problem. One of the most widely used methods of dealing with multiple conflicting objectives consists of constructing and optimizing a so-called achievement scalarizing function (ASF) which has an ability to produce any Pareto optimal or weakly/properly Pareto optimal solution. The ASF minimizes the distance from the reference point to ...

Although a pilot national live-donor kidney exchange program was recently launched in the US, the kidney shortage is increasing faster than ever. A new solution paradigm is able to incorporate compatible pairs in exchange. In this paper, we consider an exchange framework that has both compatible and incompatible pairs, and patients are indifferent over compatible pairs. Only two-way exchanges a...

Since the beginning of Nineties, research and application of multi-objective evolutionary algorithms (MOEAs) have found increasing attention. This is mainly due to the ability of evolutionary algorithms to find multiple Pareto-optimal solutions in one single simulation run. In this paper, we present an overview of the multi-objective evolutionary algorithms and then discuss a particular algorit...

This paper presents a new multiobjective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem. The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new Strength Pareto Evolutionary Algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective problem with competing and non-commensurable objectives....

We propose a multi-agent based utilitarian approach to model and understand information flows in social networks that lead to Pareto optimal informational exchanges. We model the individual expected utility function of the agents to reflect the net value of information received. We show how this model, adapted from a theorem by Karl Borch dealing with an actuarial Risk Exchange concept in the I...

Biologically inspired computation has been recently used with mathematical models towards the design of new synthetic organisms. In this work, we use Pareto optimality to optimize these organisms in a multi-objective fashion. We infer the best knockout strategies to perform specific tasks in bacteria, which involve concurrent maximization/minimization of multiple functions (codomain) and optimi...

When we try to implement a multi-objective genetic algorithm (MOGA) with variable weights for finding a set of Pareto optimal solutions, one difficulty lies in determining appropriate search directions for genetic search. In our MOGA, a weight value for each objective in a scalar fitness function was randomly specified. Based on the fitness function with the randomly specified weight values, a ...