In terms of flexibility and product variety in lot-sizing systems of crisp cases, the average demand of per unit of time (mj), the relative duration of setup (qj), and the unit cost of production (cj) are considered. Instead of using the usual method that the mj, qj, and cj in the total cost function are respectively fuzzified by the triangular fuzzy numbers to derive fuzzy total cost, in this ...

An interval type-2 fuzzy set (IT2FS) contains the infinite number of embedded membership functions (MFs) defined as type-1 sets. The center gravity (COG) an IT2FS is obtained by integrating centroids all these MFs. However, obtaining COG in a continuous domain impossible because MFs and, discrete domain, comes with exponential time complexity. Therefore, different algorithms were proposed to fi...

Numerical algorithms are developed for the centroid molecular dynamics (centroid MD) method to calculate dynamical time correlation functions for general many-body quantum systems. Approaches based on the normal mode path integral molecular dynamics and staging path integral Monte Carlo methods are described to carry out a direct calculation of the force on the centroid variables in the centroi...

Unsupervised competitive learning algorithms for clustering of sensor nodes in wireless sensor networks are evaluated with a large scale data set in this paper. The Centroid Neural Network (CNN) is compared with Fuzzy c-Means (FCM) algorithm in determining cluster heads among given sensor nodes. The cluster heads are combined with Low Energy Adaptive Clustering Hierarchy (LEACH) for minimizing ...

Like k-means and Gaussian mixture model (GMM), fuzzy c-means (FCM) with soft partition has also become a popular clustering algorithm still is extensively studied. However, these algorithms their variants suffer from some difficulties such as determination of the optimal number clusters which key factor for quality. A common approach overcoming this difficulty to use trial-and-validation strate...

They appear often situations in a system's operation characterized by a degree of vagueness and/or uncertainty. In the present paper, the author uses principles of fuzzy logic to develop a general model representing such kind of situations. They also present three alternative methods for measuring a fuzzy system's effectiveness, including the use of its total possibilistic uncertainty, the clas...

This paper analysis single-period inventory models with discrete demand under fuzzy environment. In the proposed models three different cases are examined. In the first case, demand is represented by a triangular fuzzy number and a discrete membership function. In the second case, demand is a stochastic variable while inventory costs such as unit holding cost and unit shortage cost are imprecis...