Fuzzy Demand Rate Research Articles

A Study of an EOQ Model of Deteriorated Items with Pentagonal Dense Fuzzy Demand Rate

In this project work, we deal with an economic order quantity inventory model of deteriorating items under non-random uncertain demand. Here we consider the customers screen the fresh items during the selling period. After a certain period of time, the deteriorated items are sold at a discounted price. Firstly, we solve the crisp model, and then the model is converted into a fuzzy environment. Here we consider the pentagonal dense fuzzy, trapezoidal dense fuzzy, and triangular dense fuzzy for a comparative study. We have taken the numerical result using LINGO 18.0 software. Finally, sensitivity analysis and graphical illustration have been given to check the validity of the model.

Optimal Procurement of COVID-19 Vaccine with Time-Dependent Holding Cost and Shortages under Cloud Fuzzy Demand Rate

COVID-19 vaccine has emerged as the most powerful weapon against the spread of the coronavirus. Therefore, the management of the vaccine inventory is undoubtedly the most influential and important task for the global distribution of the vaccine. This paper is an attempt to model the vaccine inventory system having time-varying holding costs and partially backlogged shortages. The concept of fuzzy set and cloud pentagonal fuzzy number has been incorporated to make the models more realistic and applicable. Models are solved and validated through numerical examples and graphical representation. Further, sensitivity analysis has been done to identify the most sensitive parameters of all. Finally, managerial insights and conclusions have been drawn to make the vaccine inventory system more robust.

Fuzzy optimisation of a production model with CNTFN demand rate under trade-credit policy

The presented article deals with an economic production quantity model with a trade-credit policy. The classical (crisp) model presented with a fuzzy demand rate under a cloudy fuzzy environment. The concept of fuzziness affects the inventory model as well as inventory cost, profit, lot size, and all other factors. The centroid method has been used for the defuzzification of the model with triangular fuzzy demand in a general fuzzy environment. To avoid the effect of non-random uncertainties of demand rate in the production, the cloudy fuzzy model has been used here to provide a profitable business under several circumstances. And the Yager's ranking method has been used for defuzzification for the cloudy fuzzy model. The cloudy fuzzy model gives better results instead of deterministic models for the long-run production cycle. Finally, the sensitivity analysis and graphical illustrations of a numerical example justify the model.

FEOQ model with octagonal fuzzy demand rate and optimize with signed distance method

Uncertainties in the stock control system development is one of the main concerns of researchers, several studies has been done in this research field with different fuzzy numbers by using different defuzzification methods. In this present article, at first, we have studied the scenario of increasing demand rate with the time and shortage are fully backlogged. Due to some reasons, there is flexible(uncertain) demand rate for the production, so the demand rate has to be taken as octagonal fuzzy number and the model converted into fuzzy model. The purpose of presented model is to optimize the total inventory cost in both the crisp and the fuzzy situations. The designated model included with Signed distance method for an appropriate numerical example, sensitivity analysis and graphical illustration for better explanation of the article.

An EOQ Model based on Intuitionistic Fuzzy and Cloudy Intuitionistic Fuzzy Demand Rate

An EOQ Model based on Intuitionistic Fuzzy and Cloudy Intuitionistic Fuzzy Demand Rate

A study of an EOQ model with public-screened discounted items under cloudy fuzzy demand rate

This article deals with an economic order quantity inventory model of imperfect items under non-random uncertain demand. Here we consider the customers screen the imperfect items during the selling period. After a certain period of time, the imperfect items are sold at a discounted price. We split the model into three cases, assuming that the demand rate increases, decreases, and is constant in the discount period. Firstly, we solve the crisp model, and then the model is converted into a fuzzy environment. Here we consider the dense fuzzy, parabolic fuzzy, degree of fuzziness and cloudy fuzzy for a comparative study. The basic novelty of this paper is that a computer-based algorithm and flow chart have been given for the solution of the proposed model. Finally, sensitivity analysis and graphical illustration have been given to check the validity of the model.

A comprehensive study of a backlogging EOQ model with nonlinear heptagonal dense fuzzy environment

This paper deals with an adaptation of an application of nonlinear heptagonal dense fuzzy number. The concept of linear and as well as non-linear for both symmetric and asymmetric heptagonal dense fuzzy number is introduced here. We develop a new ranking method for non-linear heptagonal dense fuzzy number also. Considering a backorder inventory model with non-linear heptagonal dense fuzzy demand rate we have utilized a modified centroid method for defuzzification. For decision maker’s aspects, numerical examples, comparative study with other dense fuzzy numbers and a sensitivity analysis show the superiority of the nonlinear heptagonal dense fuzzy number. Finally, graphical illustrations are made to justify the model followed by a conclusion.

A comprehensive study of an economic order quantity model under fuzzy monsoon demand

This article deals with a classical economic order quantity (EOQ) model under monsoon type fuzzy demand rate. It is nothing but the generalization of cloudy fuzzy model. We split the EOQ model into three parts according to the real-time fuzzy components of the demand rate. To defuzzify the model we develop an algorithm and the solution is obtained with the help of a nonlinear optimization technique that requires maximum aspiration level of the fuzzy membership of the objective function. Moreover, for comparative study we take numerical results of the crisp, general fuzzy and cloudy fuzzy model also. By this study we have shown that the decision maker might have to choose the monsoon type fuzzy environment all the time to control the proposed inventory. Moreover, sensitivity analysis and graphical illustrations are made to justify the new fuzzy approach.

Two Decision Makers' Single Decision over a Back Order EOQ Model with Dense Fuzzy Demand Rate

Two Decision Makers' Single Decision over a Back Order EOQ Model with Dense Fuzzy Demand Rate

Two decision makers’ single decision over a back order EOQ model with dense fuzzy demand rate

<p>In this article we develop an economic order quantity (EOQ) model with backlogging where the decision is made jointly from two decision maker supposed to view one of them as the industrialist (developer) and the other one as the responsible manager. The problem is handled under dense fuzzy environment. In fuzzy set theory the concept of dense fuzzy set is quite new which is depending upon the number of negotiations/ turnover made by industrial developers with the supplier of raw materials and/or the customers. Moreover, we have discussed the preliminary concept on dense fuzzy sets with their corresponding membership functions and appropriate defuzzification method. The numerical study explores that the solution under joint decision maker giving the finer optimum of the objective function. A sensitive analysis, graphical illustration and conclusion are made for justification the new approach.</p>

Two decision makers’ single decision over a back order EOQ model with dense fuzzy demand rate

<p>In this article we develop an economic order quantity (EOQ) model with backlogging where the decision is made jointly from two decision maker supposed to view one of them as the industrialist (developer) and the other one as the responsible manager. The problem is handled under dense fuzzy environment. In fuzzy set theory the concept of dense fuzzy set is quite new which is depending upon the number of negotiations/ turnover made by industrial developers with the supplier of raw materials and/or the customers. Moreover, we have discussed the preliminary concept on dense fuzzy sets with their corresponding membership functions and appropriate defuzzification method. The numerical study explores that the solution under joint decision maker giving the finer optimum of the objective function. A sensitive analysis, graphical illustration and conclusion are made for justification the new approach.</p>

Decision of a Fuzzy Inventory with Fuzzy Backorder Model Under Cloudy Fuzzy Demand Rate

This paper deals with the classical backorder economic order quantity inventory model under cloudy fuzzy environment. The traditional concepts on fuzziness of the fuzzy parameters remains the same in all the time, but in practice, due to the human experience and precision the fuzziness began to remove from the system over time. However, we take the crisp model first, then fuzzifying the model to get a decision under the cloudy fuzzy (extension of dense fuzzy) demand rate followed by its practical application. A new defuzzification method has been utilized for ranking the fuzzy numbers. Finally, comparative analysis between the crisp, general fuzzy as well as cloudy fuzzy solutions are done extensively. The graphical illustrations and numerical examples are studied to justify the usefulness of the new approach in the model itself.

A Fuzzy Reverse Logistics Inventory System Integrating Economic Order/Production Quantity Models

This paper develops a reverse inventory model where the recoverable manufacturing process is affected by the learning theory. We propose the inclusion of the fuzzy demand rate of the serviceable products and the fuzzy collection rate of the recoverable products from customers in the total cost function of the model. Two popular defuzzification methods, namely the signed distance technique, a ranking method for fuzzy numbers, and the graded mean integration representation method are employed to find the estimate of the total cost function per unit time in the fuzzy sense. We provide a comprehensive numerical example to illustrate and compare the results obtained by the two mentioned defuzzification methods. This is one of the only few attempts in the related literature comparing the performance of these methods with the effect of the fuzziness of both of the demand and the collection rate in the presence of the learning simultaneously. The results indicate that deciding on which method could be used depends on the target strategy that could focus on the total cost, ordering lot size, or recovery lot size.

A two-warehouse inventory model with fuzzy deterioration rate and fuzzy demand rate under conditionally permissible delay in payment

The classical inventory models usually consider deterioration rate and demand rate as constant quantities, but, in the practical situations, the deterioration rate and the demand rate are uncertain in nature. In this paper, a new two-warehouse inventory model with fuzzy deterioration rate and fuzzy demand rate under conditionally permissible delay in payment is developed. The deterioration rate and demand rate are considered as right-shaped fuzzy numbers. The objective was to obtain the optimum value of the fuzzy total cost. The numerical examples are also considered to compare the crisp model and its corresponding fuzzy model. Finally, a sensitivity analysis is carried out to get the sensitiveness of the tolerance of different input parameters.

An integrated supply chain model for the perishable items with fuzzy production rate and fuzzy demand rate

In the changing market scenario, supply chain management is getting phenomenal importance amongst researchers. Studies on supply chain management have emphasized the importance of a long-term strategic relationship between the manufacturer, distributor and retailer. In the present paper, a model has been developed by assuming that the demand rate and production rate as triangular fuzzy numbers and items deteriorate at a constant rate. The expressions for the average inventory cost are obtained both in crisp and fuzzy sense. The fuzzy model is defuzzified using the fuzzy extension principle, and its optimization with respect to the decision variable is also carried out. Finally, an example is given to illustrate the model and sensitivity analysis is performed to study the effect of parameters.

Production lot-size model with fuzzy production rate and fuzzy demand rate for deteriorating item under permissible delay in payments

A fuzzy production lot-size inventory model with a permissible delay in payments is developed by assuming that the demand rate and the production rate are triangular fuzzy numbers and the items deteriorate at a constant rate θ. The expressions for the average inventory cost both in the crisp sense and fuzzy sense are derived. The fuzzy model is defuzzified using fuzzy extension principle and its optimization with respect to the decision variables is carried out. The computation procedure is explained with help of a numerical example. Sensitivity of the optimal solution to changes in parameter values is examined.

An economic production quantity inventory model involving fuzzy demand rate and fuzzy deterioration rate

Generally, in deriving the solution of economic production quantity (EPQ) inventory model, we consider the demand rate and deterioration rate as constant quantity. But in case of real life problems, the demand rate and deterioration rate are not actually constant but slightly disturbed from their original crisp value. The motivation of this paper is to consider a more realistic EPQ inventory model with finite production rate, fuzzy demand rate and fuzzy deterioration rate. The effect of the loss in production quantity due to faulty/old machine have also been taken into consideration. The methodology to obtain the optimum value of the fuzzy total cost is derived and a numerical example is used to illustrate the computation procedure. A sensitivity analysis is also carried out to get the sensitiveness of the tolarance of different input parameters.

Optimization of fuzzy production inventory models

In this paper, we introduce two fuzzy production inventory models with fuzzy parameters for crisp production quantity, or for fuzzy production quantity. The fuzzy total production inventory costs of these models under the fuzzy arithmetical operations of Function Principle are proposed. The final purpose is to find optimal solutions of these models by using Graded Mean Integration Representation method for defuzzifing fuzzy total production inventory cost, and by using Extension of the Lagrangean method for solving inequality constrain problem. Furthermore, we find that the optimal solutions are all crisp real numbers. In addition, when the fuzzy parameters (fuzzy inventory cost, fuzzy demand, fuzzy setup cost, fuzzy demand rate, and fuzzy production rate) are all crisp real numbers, the optimal solutions of our proposed models can be specified to meet classical production inventory models.