Application of fuzzy optimization to a supply chain network design: A case study of an edible vegetable oils manufacturer

This study applies fuzzy sets to integrate the supply chain network of an edible vegetable oils manufacturer. The proposed fuzzy multi-objective linear programming model attempts to simultaneously minimize the total transportation costs. The first part of the total transportation costs is between suppliers and silos; and rest one is between manufacturer and warehouses. The approach incorporates all operating realities and actual flow patterns at production/distribution network with reference to demands of warehouses, capacities of tin and pet packaging lines. The model has been formulated as a multi objective linear programming model where data are modeled by triangular fuzzy numbers. Finally, the developed fuzzy model is applied for the case study, compiled the results and discussed.     

Fuzzy rule generation methods for high-level computer vision

In many decision making systems involving multiple sources, the decisions made may be considered as the result of a rule-based system in which the decision rules are usually enumerated by experts or generated by a learning process. In this paper, we discuss the various issues involved in the generation of fuzzy rules automatically from training data for high-level computer vision. Features are treated as linguistic variables that appear in the antecedent clauses of the rules. We present methods to generate the corresponding linguistic labels (values) and their membership functions. Rules are generated by constructing a minimal approximate fuzzy aggregation network and then training the network using gradient descent methods. Several examples are given.     

Fractional-order optimal fuzzy control for network delay

Fuzzy logic control has been used frequently in tuning network control system (NCS) due to its on-line dynamic static non-linear match and several remarkable fractional-order controllers have achieved satisfactory control performance when applied to NCS in present years, therefore, in this paper, a novel fractional fuzzy logic controller which combined the fractional algorithm and fuzzy logic control together has been proposed to deal with fixed and random network induced delays in closed-loop feedback systems. The comparisons of set-point tracking performances of fractional fuzzy logic PID controller (FFuzzyPID), conventional fuzzy logic PID controller(FuzzyPID), fractional optimal PID controller (FOPID), and optimal PID controller(OPID) on a representative plant with fixed and random network delays have been shown with simulations. The simulation results indicate that fractional fuzzy logic controller has higher capability to handle network delays compared with other controllers in most cases.     

Resolution of composite fuzzy relation equations based on Archimedean triangular norms

Lately, the sup-t-norm composition of fuzzy relations has been used instead of the well-known max–min. Thus, there is a need for methods of studying and solving sup-t-norm fuzzy relation equations (t is any t-norm). In this paper, the solution existence problem is first studied and solvability criteria for composite fuzzy relation equations of any t-norm are given. Then, a methodology for solving fuzzy relation equations based on sup-t composition, where t is an Archimedean t-norm, is proposed. This resolution method is simpler and faster than those proposed for covering all the continuous t-norms. The result is important, since, as is shown in the paper, the only continuous t-norm that is not Archimedean is the “minimum”.     

基于模糊因素的载人航天器乘员舱内人-机界面工效学评价研究

载人航天器乘员舱内人－机界面的工效学评价是决定能否进行载人空间飞行的重要依据之一，由于人－机界面本身的复杂性，使得对其评价有一定的难度。本文在模糊理论的基础上，首先对舱内人－机界面工效学评价各参数进行随机模糊分析，据此建立工效学模糊综合评价模型，最后进行了实例研究。结果表明，对于同一个评价对象，应用该方法更能接近实际。     

关于模糊严格偏好关系的传递性

给定一个模糊关系,Ovchinnikov和Roubens引进了非常一般的模糊严格偏好关系定义,本文将详细讨论该偏好关系的弱传递性,一致性,强传递性以及非循环性等传递性有关的性质。     

前苏联和俄罗斯模糊理论研究与应用情况概述

对前苏联20世纪80年代及苏联解体后俄罗斯20世纪90年代的模糊理论研究与应用情况作了概述,列举了在人工智能认知的模糊原理、信息论的模糊性和模糊空间、随机模糊规划、工业用综合模糊控制系统等领域的研究成果,并列出90多篇（部）俄文文献资料。     

Fuzzy幂群的基数及表示

研究Fuzzy幂群^[2]中元素的基数,证明这种Fuzzy幂群并非Zadeh意义的Fuzzy子群,而且可以用一分明群表示,给出有限群上Fuzzy幂群的正则表示,并讨论Fuzzy幂群的同态性质。     

-Difference sequence spaces of fuzzy numbers

In this paper, using the difference operator of order m and an Orlicz function, we introduce and examine some classes of sequences of fuzzy numbers. We give the relations between the strongly Cesàro type convergence and statistical convergence in these spaces. Furthermore, we study some of their properties like completeness, solidity, symmetricity, etc. We also give some inclusion relations related to these classes.     

A learning process for fuzzy control rules using genetic algorithms

The purpose of this paper is to present a genetic learning process for learning fuzzy control rules from examples. It is developed in three stages: the first one is a fuzzy rule genetic generating process based on a rule learning iterative approach, the second one combines two kinds of rules, experts rules if there are and the previously generated fuzzy control rules, removing the redundant fuzzy rules, and the thrid one is a tuning process for adjusting the membership functions of the fuzzy rules. The three components of the learning process are developed formulating suitable genetic algorithms.