Most engineering optimization uses multiple objective functions rather than single objective function. To realize an artificial life algorithm based multi-objective optimization, this paper proposes a Pareto artificial life algorithm that is capable of searching Pareto set for multi-objective function solutions. The Pareto set of optimum solutions is found by applying two objective functions fo...

We propose a new approach to convex nonlinear multiobjective optimization that captures the geometry of the Pareto set by generating a discrete set of Pareto points optimally. We show that the problem of finding an optimal representation of the Pareto surface can be formulated as a mathematical program with complementarity constraints. The complementarity constraints arise from modeling the set...

Previous research using plot-level agricultural data from Burkina Faso found that the allocation of resources within African households was Pareto inefficient, contradicting most collective models of intrahousehold bargaining. I provide an explanation for these households' Pareto inefficient behavior and I test its robustness using an alternative dataset also collected in Burkina Faso. Househol...

Abstract: The Pareto probability distribution is widely applied in different fields such us finance, physics , hydrology , geology and astronomy. This note deals with an application of the Pareto distribution to astrophysics and more precisely to the statistical analysis of mass of stars and of diameters of asteroids. In particular a comparison between the usual Pareto distribution and its trun...

Multi-objective AI planning suffers from a lack of benchmarks with known Pareto Fronts. A tunable benchmark generator is proposed, together with a specific solver that provably computes the true Pareto Front of the resulting instances. A wide range of Pareto Front shapes of various difficulty can be obtained by varying the parameters of the generator. The experimental performances of an actual ...

PURPOSE To eliminate or reduce the error to Pareto optimality that arises in Pareto surface navigation when the Pareto surface is approximated by a small number of plans. METHODS The authors propose to project the navigated plan onto the Pareto surface as a postprocessing step to the navigation. The projection attempts to find a Pareto optimal plan that is at least as good as or better than t...

Repeated play in games by simple adaptive agents is investigated. The agents use Q-learning, a special form of reinforcement learning, to direct learning of behavioral strategies in a number of 2! 2 games. The agents are able effectively to maximize the total wealth extracted. This often leads to Pareto optimal outcomes. When the rewards signals are sufficiently clear, Pareto optimal outcomes w...

Various multivariate Pareto distributions are known to exhibit the heavy tail behaviors. This paper examines the tail dependence properties of a general class of multivariate Pareto distributions with the Pareto index and some common scale parameters. The multivariate tail dependence describes the amount of dependence in the upper-orthant tail or lower-orthant tail of a multivariate distributio...

We study when two-member household choice behavior is compatible with Pareto optimality. We ask when an external observer of household choices, who does not know the individuals’ preferences, can rationalize the choices as being Pareto-optimal. Our main contribution is to reduce the problem of rationalization to a graph-coloring problem. As a result, we obtain simple tests for Pareto optimal ch...