scholarly journals The Economic Order Quantity in a Fuzzy Environment for a Periodic Inventory Model with Variable Demand

2022 ◽  
pp. 102-107
Author(s):  
K. Kalaiarasi ◽  
MARY HENRIETTA H ◽  
M. Sumathi ◽  
A. Stanley Raj
Keyword(s):  
Sensitivity Analysis ◽  
Numerical Analysis ◽  
Fuzzy Numbers ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Critical Part ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment

The technique of limiting expenditure plays a critical part in an organization's ability to govern the smooth operation of its management system. The economic order quantity (EOQ) is calculated by solving a nonlinear problem, and the best solution is investigated in a fuzzy and intuitionistic fuzzy environment. The overall cost is made up of several factors, such as demand, holding, and ordering costs. The demand and stock-out characteristics were both fuzzified using fuzzy and intuitionistic fuzzy numbers. The numerical analysis shows the comparison between the two fuzzy numbers through sensitivity analysis.

A Novel Ranking Approach to Solving Fully LR-Intuitionistic Fuzzy Transportation Problems

2018 ◽  
Vol 15 (01) ◽  
pp. 95-112 ◽  
Author(s):  
Abhishekh ◽  
A. K. Nishad
Keyword(s):  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Optimal Solution ◽  
Solution Procedure ◽  
Ranking Functions ◽  
Transportation Problems ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Fuzzy Transportation Problem

To the extent of our knowledge, there is no method in fuzzy environment to solving the fully LR-intuitionistic fuzzy transportation problems (LR-IFTPs) in which all the parameters are represented by LR-intuitionistic fuzzy numbers (LR-IFNs). In this paper, a novel ranking function is proposed to finding an optimal solution of fully LR-intuitionistic fuzzy transportation problem by using the distance minimizer of two LR-IFNs. It is shown that the proposed ranking method for LR-intuitionistic fuzzy numbers satisfies the general axioms of ranking functions. Further, we have applied ranking approach to solve an LR-intuitionistic fuzzy transportation problem in which all the parameters (supply, cost and demand) are transformed into LR-intuitionistic fuzzy numbers. The proposed method is illustrated with a numerical example to show the solution procedure and to demonstrate the efficiency of the proposed method by comparison with some existing ranking methods available in the literature.

scholarly journals A Value and Ambiguity-Based Ranking Method of Trapezoidal Intuitionistic Fuzzy Numbers and Application to Decision Making

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Xiang-tian Zeng ◽  
Deng-feng Li ◽  
Gao-feng Yu
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Implementation Process ◽  
Ranking Method ◽  
Comparison Analysis ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
A Value ◽  
Trapezoidal Intuitionistic Fuzzy Numbers

The aim of this paper is to develop a method for ranking trapezoidal intuitionistic fuzzy numbers (TrIFNs) in the process of decision making in the intuitionistic fuzzy environment. Firstly, the concept of TrIFNs is introduced. Arithmetic operations and cut sets over TrIFNs are investigated. Then, the values and ambiguities of the membership degree and the nonmembership degree for TrIFNs are defined as well as the value-index and ambiguity-index. Finally, a value and ambiguity-based ranking method is developed and applied to solve multiattribute decision making problems in which the ratings of alternatives on attributes are expressed using TrIFNs. A numerical example is examined to demonstrate the implementation process and applicability of the method proposed in this paper. Furthermore, comparison analysis of the proposed method is conducted to show its advantages over other similar methods.

scholarly journals Group Replacement Strategy under Fuzzy Methods

2019 ◽  
Vol 9 (1S5) ◽  
pp. 250-254
Keyword(s):  
Fuzzy Numbers ◽  
Optimal Solution ◽  
Active Role ◽  
Replacement Policy ◽  
Replacement Strategy ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Methods ◽  
Fuzzy Environment

Intuitionistic Fuzzy Numbers play an active role in finding an optimal solution for replacement problems under vague and uncertain situations. This paper gives a group replacement policy under fuzzy environment. Here all the costs and the number of units are taken as Triangular Intuitionistic Fuzzy Numbers (TIFNs). An example is used for illustration of the policy

scholarly journals Economic Order Quantity for Items with Two Types of Imperfect Quality

2011 ◽  
Vol 2 (1) ◽  
pp. 73-82 ◽  
Author(s):  
Muhammad AL-SALAMAH ◽  
Omar ALSAWAFY
Keyword(s):  
Numerical Analysis ◽  
Probability Density ◽  
Probability Density Functions ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Density Functions ◽  
Order Quantity ◽  
Imperfect Quality ◽  
Classical Economic ◽  
Single Batch

The classical economic order quantity considers that the ordered items are of perfect quality. In this research, a model for the economic order quantity of imperfect quality items is developed, where the incoming lot has fractions of scrap and reworkable items. These fractions are considered to be random variables with known probability density functions. The demand is satisfied from perfect items and reworked items; whereas the scrap items are sold in a single batch at the end of the cycle with a salvage cost. A numerical analysis is provided to illustrate the sensitivity of the model to the fractions of scrap and reworked items.

scholarly journals Normalized Weighted Bonferroni Harmonic Mean-Based Intuitionistic Fuzzy Operators and Their Application to the Sustainable Selection of Search and Rescue Robots

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 218 ◽  
Author(s):  
Jinming Zhou ◽  
Tomas Baležentis ◽  
Dalia Streimikiene
Keyword(s):  
Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Real Life ◽  
Aggregation Operators ◽  
Harmonic Mean ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Selection Of

In this paper, Normalized Weighted Bonferroni Mean (NWBM) and Normalized Weighted Bonferroni Harmonic Mean (NWBHM) aggregation operators are proposed. Besides, we check the properties thereof, which include idempotency, monotonicity, commutativity, and boundedness. As the intuitionistic fuzzy numbers are used as a basis for the decision making to effectively handle the real-life uncertainty, we extend the NWBM and NWBHM operators into the intuitionistic fuzzy environment. By further modifying the NWBHM, we propose additional aggregation operators, namely the Intuitionistic Fuzzy Normalized Weighted Bonferroni Harmonic Mean (IFNWBHM) and the Intuitionistic Fuzzy Ordered Normalized Weighted Bonferroni Harmonic Mean (IFNONWBHM). The paper winds up with an empirical example of multi-attribute group decision making (MAGDM) based on triangular intuitionistic fuzzy numbers. To serve this end, we apply the IFNWBHM aggregation operator.

scholarly journals The Fuzzy Economic Order Quantity Problem with a Finite Production Rate and Backorders

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Kaj-Mikael Björk
Keyword(s):  
Fuzzy Numbers ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Economic Production Quantity ◽  
Eoq Models ◽  
Economic Production ◽  
Epq Model ◽  
Production Quantity ◽  
Industrial Context

The track of developing Economic Order Quantity (EOQ) models with uncertainties described as fuzzy numbers has been very lucrative. In this paper, a fuzzy Economic Production Quantity (EPQ) model is developed to address a specific problem in a theoretical setting. Not only is the production time finite, but also backorders are allowed. The uncertainties, in the industrial context, come from the fact that the production availability is uncertain as well as the demand. These uncertainties will be handled with fuzzy numbers and the analytical solution to the optimization problem will be obtained. A theoretical example from the process industry is also given to illustrate the new model.

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