We study the problem of computing the diameter of a set of n points in d-dimensional Euclidean space for a  xed dimension d, and propose a new (1 + ")-Approximation algorithm with O(n + 1="d􀀀 1) time and O(n) space, where 0 < " 6 1. We also show that the proposed algorithm can be modi ed to a (1 + O("))-Approximation algorithm with O(n + 1=" 2d 3 􀀀 1 2 ) running time. Our proposed Algorithms are di erent with the previous Algorithms in terms of computational technique and data structures. These results provide some improvements in comparison with existing Algorithms in terms of simplicity and data structure.

‎‎‎Given a fuzzy normed space, we will introduce the notion of fuzzy near best Approximation as a generalization of the notion of fuzzy best Approximation. Some basic properties are characterized and also many examples for illustration are presented. Also, the hereditary properties of the fuzzy near best Approximation on direct sum and tensor product of linear spaces are discussed.