the starting point of this paper is given by priestley’s papers, where a theory of representation of distributive lattices is presented. the purpose of this paper is to develop a representation theory of fuzzy distributive lattices in the finite case. in this way, some results of priestley’s papers are extended. in the main theorem, we show that the category of finite fuzzy priestley space...

In this paper, we present a simplex method for linear programs in standard form, or more precisely, linear optimization problems that have countably many non-negative variables and countably many equality constraints. Important special cases of these problems include infinite horizon deterministic dynamic programming problems and network flow problems with countably infinite nodes and arcs. Aft...

— We identify the best root node strategy for the approximation of the time-indexed bound in min-sum scheduling by sorting through various options that involve the primal simplex, dual simplex, and barrier methods for linear programming, the network simplex method for network ow problems, and DantzigWolfe decomposition and column generation. Note to Practitioners— Min-sum scheduling problems ar...

Fuzzy numbers are used in various fields such as fuzzy process methods, decision control theory, problems involving making, and systematic reasoning. systems, including set theory. In this paper, pentagonal variables (PFV) to formulate linear programming (LPP). Here, we will concentrate on an approach addressing these issues that uses the simplex technique (SM). Linear (LPP) with (PFN) two basi...

Overview material for the Special Session (Tuning Fuzzy Controllers Using Adaptive Critic Based Approximate Dynamic Programming) is provided. The Dual Heuristic Programming (DHP) method of Approximate Dynamic Programming is described and used to the design a fuzzy control system. DHP and related techniques have been developed in the neurocontrol context but can be equally productive when used w...

Sets of desirable gambles provide a general representation of uncertainty which can handle partial information in a more robust way than precise probabilities. Here we study the effectiveness of linear programming algorithms for determining whether or not a given set of desirable gambles avoids sure loss (i.e. is consistent). We also suggest improvements to these algorithms specifically for che...

In this paper, we define the notion of (dual) multi-fuzzy normedspaces and describe some properties of them. We then investigate Ulam-Hyers stability of Jensen's functional equation for mappings from linear spaces into  multi-fuzzy normed spaces. We establish an asymptotic behavior of the Jensen equation in the framework of multi-fuzzy normed spaces.

Speech detection and speech recognition are two important classification problems in human-robot interaction. They are easily affected by the noisy environment. To solve this problem, a dual-discriminability-analysis Type-2 fuzzy neural network (DDA2FNN) is proposed. In handing problems with uncertainties such as noisy data, Type-2 fuzzysystems generally outperform their Type-1 counterparts. He...

In many scientific and engineering applications, the fuzzy set concept plays an important role. The fuzziness appears when we need to perform, on manifold, calculations with imprecision variables. The fuzzy set theory was introduced initially by Zadeh [1] in 1965. In the theory and applications of fuzzy sets, convexity is a most useful concept. In fact, in the basic and classical paper [1], Zad...

The fuzzy rough sets and generalized fuzzy rough sets have been extended by three pairs of fuzzy logical operators to deal with real-valued data for a variety of models. Three pairs of fuzzy logical operators are triangular norm or t-norm and its dual (t-conorm), residual implicator or R-implicator and its dual, fuzzy implicator and t-norm, which are frequently discussed in generalization model...