This paper addresses the problem of the optimal design of batch plants with imprecise demands and proposes an alternative treatment of the mprecision by using fuzzy concepts. For this purpose, we extended a multiobjective genetic algorithm (MOGA) developed in previous works, taking nto account simultaneously maximization of the net present value (NPV) and two other performance criteria, i.e. th...

A new multiobjective selection procedure for Genetic Algorithms based on the paradigms of fuzzy logic is discussed and compared to the niched Pareto selection procedure. In the example presented here the fuzzy logic procedure optimized the parameters of a series of functions in a more efficient manner than the niched Pareto approach. The main advantage that the fuzzy logic approach has over the...

In a preceding contribution, we conducted a study considering a fuzzy multiclassifier system (MCS) design framework based on Fuzzy Unordered Rule Induction Algorithm (FURIA). It served as the fuzzy rule classification learning algorithm to derive the component classifiers considering bagging and feature selection. In this work, we integrate this approach under the overproduce-and-choose strateg...

In this paper, we formulate a multiobjective fuzzy random simple recourse programming problem, in which fuzzy random variables coefficients are involved in equality constraints. In the proposed method, equality constraints with fuzzy random variables are defined on the basis of a possibility measure and and a two-stage programming method. For a given permissible possibility level specified by t...

The purpose of this paper is to study vendor selection problem with multi-vendor and multi-item in iron & steel industry. Firstly, the native fuzziness, derived from some uncertainty information, of some parameters in decision-making objectives is analyzed. After that, a fuzzy multiobjective programming model is formulated, with procurement quantity as decision variable, minimizing the net cost...

Analysis of 〈X,R〉 models is considered as part of a general approach to solving optimization problems with fuzzy coefficients. This approach involves a modification of traditional optimization methods and is associated with formulating and solving one and the same problem within the framework of mutually interrelated models by constructing equivalent analogs with fuzzy coefficients in objective...

In this paper, we focus on multiobjective fuzzy random programming problems with simple recourse through a fractile optimization model, in which fuzzy random variables coefficients are involved in equality constraints, and random variables coefficients are involved in the objective functions. In the proposed method, equality constraints with fuzzy random variables are defined on the basis of a ...