This paper presents a Semi-Supervised Feature Selection Method based on a univariate relevance measure applied to a multiobjective approach of the problem. Along the process of decision of the optimal solution within Pareto-optimal set, atempting to maximize the relevance indexes of each feature, it is possible to determine a minimum set of relevant features and, at the same time, to determine ...

A simple proof of the equivalence of Pareto optimality plus positiveness and α-maxmin optimality, dispensing with the assumption of closedness of the utility possibility set, is given. Also the structure of the set of Pareto optimal utility profiles is studied. © 2008 Elsevier B.V. All rights reserved. The main results of the recent paper by Sagara ‘‘A characterization of α-maxmin solutions of ...

Our aim in this paper is to prove geometric characterizations of the free disposal condition for nonconvex economies on infinite dimensional commodity spaces even if the cone and the production set involved in the condition have an empty interior such as in L1 with the positive cone L+. We then use this characterization to prove the existence of Pareto and weak Pareto optimal points. We also ex...

We propose a multi-objective machine learning approach guaranteed to find the Pareto optimal set of hybrid classification models consisting of comprehensible and incomprehensible submodels. The algorithm run-times are below 1 s for typical applications despite the exponential worst-case time complexity. The user chooses the model with the best comprehensibilityaccuracy trade-off from the Pareto...

This work presents a new learning scheme for improving generalization of Multilayer Perceptrons (MLPs). The proposed Multi-objective algorithm (MOBJ) approach minimizes both the sum of squared error and the norm of network weight vectors to obtain the Pareto-optimal solutions [1]. Preliminar results are shown in [3]. Since the Pareto-optimal solutions are not unique, we need a decision phase in...

Fix a Pareto optimal, strategy proof and non-bossy deterministic matching mechanism and define a random matching mechanism by assigning agents to the roles in the mechanism via a uniform lottery. Given a profile of preferences, the lottery over outcomes that arises under the random matching mechanism is identical to the lottery that arises under random serial dictatorship, where the order of di...

This paper presents a new search procedure to tackle multi-objective traveling salesman problem (TSP). This procedure constructs the solution attractor for each of the objectives respectively. Each attractor contains the best solutions found for the corresponding objective. Then, these attractors are merged to find the Pareto-optimal solutions. The goal of this procedure is not only to generate...

This paper discusses an improved method for solving multiple objective optimal control (MOOC) problems, and efficiently obtaining the set of Pareto optimal solutions. A general MOOC procedure has been introduced in Logist et al. [2007], to derive optimal generic temperature profiles for a steady-state tubular plug flow reactor. This procedure is based on a weighted sum of the different costs, a...

PURPOSE The current inverse planning methods for intensity modulated radiation therapy (IMRT) are limited because they are not designed to explore the trade-offs between the competing objectives of tumor and normal tissues. The goal was to develop an efficient multiobjective optimization algorithm that was flexible enough to handle any form of objective function and that resulted in a set of Pa...