Welfare economics provides the basis for judging the achievements of markets and policy makers in allocating resources. Its most powerful conceptual tool is the utility possibility frontier. This defines the set of utility allocations that can be achieved in a society subject to the constraints of tastes and technologies. Any allocation on the frontier cannot be Pareto dominated and hence would...

This paper explores how current planners behave when exposed to multiple metrics, examining which of the planners are metric sensitive and which are not. For the metric insensitive planners we propose a new method of simulating metric sensitivity for the purpose of generation of diverse plans close to a pareto frontier. It is shown that metric sensitive planners are good candidates for generati...

This paper characterizes the utility possibility frontier resulting in a model of private voluntary provision of a public good. It is shown that ex-ante lotteries over resource distributions among the agents can be Pareto improving. A corollary is that an equal distribution of resources among the agents, or any distribution where all agents contribute in equilibrium, is always Pareto dominated ...

In this paper, we propose to integrate particle swarm optimization algorithm into cultural algorithms frame to develop a more efficient cultural particle swarm algorithms (CPSA) for constrained multi-objective optimization problem. In our CPSA, the population space of cultural algorithms consists of n+1 subswarms which are used to search for the n single-objective optimums and an additional mul...

In this paper, several new set quality metrics are introduced that can be used to evaluate the ‘‘goodness’’ of an observed Pareto solution set. These metrics, which are formulated in closed-form and geometrically illustrated, include hyperarea difference, Pareto spread, accuracy of an observed Pareto frontier, number of distinct choices and cluster. The metrics should enable a designer to eithe...

This paper proposes a novel approach to generate a uniform distribution of the optimal solutions along the Pareto frontier. We make use of a standard mathematical technique for optimization namely line search and adapt it so that it will be able to generate a set of solutions uniform distributed along the Pareto front. To validate the method, numerical bi-criteria examples are considered. The m...

We consider a general framework where each agent has an outside option of privately known value. First, we show that if the designer seeks to (weakly) Pareto-improve an individually rational and participation-maximal benchmark mechanism, there is at most one strategy-proof candidate. Consequently, many known mechanisms are on the Pareto frontier of strategy-proof mechanisms. Second, we characte...

The use of evolutionary strategies (ESs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based approaches, ESs offer a means to find a set of Pareto-optimal solutions in a single run. Differential Evolution (DE) is an ES that was developed to handle optimization problems over continuous domains. Th...

This paper investigates the use of a multi-objective approach for evolving artificial neural networks that act as controllers for the legged locomotion of a 3-dimensional, artificial quadruped creature simulated in a physics-based environment. The Pareto-frontier Differential Evolution (PDE) algorithm is used to generate a pareto optimal set of artificial neural networks that optimizes the conf...

The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as Multi-objective Optimization Problems (MOPs)) has attracted much attention recently. Being population based approaches, EAs offer a means to find a group of pareto-optimal solutions in a single run. Differential Evolution (DE) is an EA that was developed to handle optimization problems over continuous ...