Intuitionistic fuzzy optimization: Usage of hesitation index
Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2013, Vol 10, Issue 4
Abstract
This paper presents the concept of usage of hesitation index in optimization problem under uncertainty. Our technique is an extension of idea of intuitionistic fuzzy optimization technique, proposed by Plamen P. Angelov in 1997, which is widely considered as a successful intuitionistic fuzzy optimization tool by researchers all over the world. It is well known that the advantages of the intuitionistic fuzzy optimization problems are twofold: firstly, they give the richest apparatus for formulation of optimization problems and on the other hand, the solution of intuitionistic fuzzy optimization problems can satisfy the objective(s) with bigger degree of satisfaction than the analogous fuzzy optimization problem and the crisp one. Angelov’s approach is an application of the intuitionistic fuzzy (IF) set concept to optimization problems. In his approach, the degree of acceptance is maximized while the degree of rejection is minimized. In our approach, not only the degree of acceptance is maximized and the degree of rejection is minimized but also the degree of hesitation is minimized. For the sake simplicity alone, the same problem, as studied by Angelov, is considered. Varied importance (and hence weights) to each of the degree of acceptance and the degree of rejection and the degree of hesitation have been given. Tables with these results are formulated and compared among.
Authors and Affiliations
Arindam Garai, Tapan Kumar Roy
Keywords
Related Articles
- EP ID EP650178
- DOI 10.24297/ijct.v10i4.3248
- Views 72
- Downloads 0
STATIC AND DYNAMIC BNP PARALLEL SCHEDULING ALGORITHMS FOR DISTRIBUTED DATABASE
Parallel processing is a technique of executing the multiple tasksconcurrently on different processors. Parallel processing is usedto solve the complex problems that require vast amount ofprocessing time. Task scheduling...
Development of HTTP Server for Remote Data Monitoring and Recording System
This paper focuses on development of remote data monitoring and recording system in industries. Now a days we are using many Networked embedded systems for monitoring and control the home or industrial devices.These low...
Fuzzy Mean Point Clustering using K-means algorithm for implementing the movecentroid function code
The paper focus on combination of K-Means algorithm for Fuzzy Mean Point Clustering Neural Network (FMPCNN). The algorithm is implemented in JAVA program code for implementing the movecentroid function code into FMPCNN.Â...
A novel method for secret image sharing Using nibble exchange
This paper proposes a new scheme for secret image sharing which shuffles and manipulates the nibbles (and hence the bytes) of the pixel values of the images. We have developed a new algorithm called LDRU (Left-Down-Right...
On the Cloud Web services: A Review
Cloud Computing is a constantly evolving IT generic term used to refer to various IT solutions and services provided via the internet. Precisely, cloud computing can be said to be  the delivery of scalable IT resource...