Given several different new product development projects and limited resources, this paper is concerned with the optimal allocation of resources among the projects. This is clearly a multi-objective optimization problem (MOOP), because each new product development project has both a profit expectation and a loss expectation, and such expectations vary according to allocated resources. In such a...

Many real-world control applications, from economics to robotics, are characterized by the presence of multiple conflicting objectives. In these problems, the standard concept of optimality is replaced by Pareto–optimality and the goal is to find the Pareto frontier, a set of solutions representing different compromises among the objectives. Despite recent advances in multi–objective optimizati...

Generalizations of Pareto optimality have been studied by a number of authors. In finite dimensions such work is exemplified by Corley [ 5 ], DaCunha and Polak [10], Goeffrion [131, Hartley [151, Lin [171, Tanino and Sawaragi [211, Wendell and Lee [221, and Yu [231. The optimization of functions into possibly infinite dimensions has been considered by Borwein [21, Cesari and Suryanarayana [31, ...

The notion of optimality and its feasibility are revisited in the context of behavior-based control. It is argued that optimal behavior is not feasible for real-world applications. As an alternative to optimality I promote Pareto-optimal and satissc-ing solutions which correspond to eecient and`good enough' behavior. It is then demonstrated that multiple objective decision theory provides a sui...

Price of Anarchy measures the welfare loss caused by selfish behavior: it is defined as the ratio of the social welfare in a socially optimal outcome and in a worst Nash equilibrium. A similar measure can be derived for other classes of stable outcomes. In this paper, we argue that Pareto optimality can be seen as a notion of stability, and introduce the concept of Price of Pareto Optimality: t...

In this work, we propose integral global optimality conditions for multiobjective problems not necessarily differentiable. The characterization, already known single objective problems, are extended to by weighted sum and Chebyshev scalarizations. Using last scalarization, an algorithm obtaining approximation of the weak Pareto front whose effectiveness is illustrated solving a collection test ...

This paper studies the efficiency of equilibria in a productive OLG economy where the process of financial intermediation is characterized by costly state verification. Both competitive equilibria and Constrained Pareto Optimal allocations are characterized. It is shown that market outcomes can be socially inefficient, even when a weaker notion than Pareto optimality is considered.

This paper deenes a class of spaces which are easy for genetic algorithms and hard for stochastic hill{climbers. These spaces require genetic recombination for successful search and are partially deceptive. Problems where tradeoos need to be made subsume spaces with these properties. Preliminary results comparing a genetic algorithm without crossover against one with two{point crossover support...

An abstract argumentation framework and the semantics, often called Dungean semantics, give a general framework for nonmonotonic logics. In the last fifteen years, a great number of papers in computational argumentation adopt Dungean semantics as a fundamental principle for evaluating various kinds of defeasible consequences. Recently, many papers address problems not only with theoretical reas...

We analyze the interaction between risk sharing and capital accumulation in a stochastic OLG model with production. We give a complete characterization of interim Pareto optimal competitive equilibrium allocations. Furthermore, we provide tests of Pareto optimality/suboptimality based on (risky) rates of return only. © 2007 Elsevier Inc. All rights reserved. JEL classification: D61; D91; E13; E43