Fuzzy Inventory Model Research Articles

Fuzzy inventory model for breakable items, including damage costs and inspection errors in a green environment.

Abstract Conventional Economic Order Quantity (EOQ) models operate on the implicit assumption that all received products are flawless. Current EOQ models for items of defectiveness implicitly suggest that suppliers do not conduct a comprehensive assessment, even though they loosen this presumption and are more applicable to scenarios in reality.This paper presents a significant EOQ model. This model takes into account errors in determining whether an item is perfect or broken. Because things are piled high in stock, breaking of products takes place. These goods are stored and sold at once, with damage costs included. Moreover, Governments have prioritized reducing carbon emissions as their main goal. With the aim of creating a greener environment, we have taken carbon emission costs into account in order to minimize overall costs and maximize overall profit. This model is distinct because it closes the research gap by taking into account breakable items under inspection errors with damage cost, and carbon emission cost.The ideal total cost of the EOQ model is produced by the crisp version. It is important to note that this model is constructed in a fuzzy manner by using a triangular fuzzy number to represent the cost of accepting a broken object.Applications of this idea include shipping commodities. A numerical illustration of the ideal solution is given and the current study addresses how changes in a few parameters influence the ideal overall cost.

Fuzzy Non-Linear Programming for Fuzzy Inventory Model with Storage Space and Budget Constraint

Fuzzy Non-Linear Programming for Fuzzy Inventory Model with Storage Space and Budget Constraint

Fuzzy inventory model with warehouse limits and carbon emission

Fuzzy inventory model with warehouse limits and carbon emission

Neutrosophic Inventory Management: A Cost-Effective Approach

Abstract Classical inventory models (IM) serve as quantitative tools for determining the optimal order quantities, timing of orders, and safety stock levels for specific inventory items or item groups. Zadeh (1965. Fuzzy sets. Information and Control, 8, 338–353) introduced fuzzy theory and Dubois and Parade (1988. Fuzzy logic in expert systems: The role of uncertainty management. Fuzzy Sets and Systems, 28, 3–17) presented the study of fuzzy inventory model, which, however, exhibits limitations in effectively handling uncertainty, inaccuracies, and imprecise data. In 1999, Smarandache presented the idea of neutrosophic set theory to handle uncertainty. Using trapezoidal neutrosophic numbers, this study extends the idea of neutrosophic sets to inventory management, concentrating on resolving the uncertainty associated with holding costs, ordering costs, and shortage costs. First time within the literature of the neutrosophic set, our new method not only addresses existing problems but can also tackle other issues that no other authors have successfully resolved so far. Additionally, we conduct a comparative analysis of our proposed model against existing models in this article. Based on this comparative study, our findings assert the superior performance of our proposed model in relation to some of the existing models. In conclusion, we wrap up our research by presenting graphical, logical, and tabular comparisons with the existing methods.

A study on periodic deteriorating linguistic fuzzy inventory model with natural idle time and imprecise demand using GSA

A study on periodic deteriorating linguistic fuzzy inventory model with natural idle time and imprecise demand using GSA

Fuzzy Inventory Model for Deteriorating Items With Low Carbon Emission Cost Under Preservation Technology and Trade Credit

Fuzzy Inventory Model for Deteriorating Items With Low Carbon Emission Cost Under Preservation Technology and Trade Credit

PENERAPAN MODEL INVENTORI PROBABILISTIK FUZZY MULTIOBJEKTIF PADA SISTEM PERSEDIAAN BUAH SALAK

Inventory control is very important in production and trading activities. The purpose of inventory control is to maintain product availability. In certain cases, the products provided must be ordered from distributors outside the city and require waiting time from the time the order is placed until the product is received. The Multiobjective Probabilistic Fuzzy Inventory model can be applied to inventory optimization problems with the uncertainty of the leadtime parameter. In this study, the model was applied to the problem of supply salak fruit at one of the distributors. The first objective function is to minimize holding costs and the second is to minimize deterioration costs. The inventory model is transformed into a single objective form using a weighted method. Based on the results, the order cycle time is 3 days with the optimal total inventory of 430.1086 kg. The holding cost and deterioration costs are IDR 2,075,866 and IDR 571,034, respectively. Changes in the weight value of the objective function result in changes in the total cost value. The greater the weight for the first objective function, the smaller the total cost.

Various Defuzzification Methods for Triangular Fuzzy Numbers Under a Fuzzy Inventory Model

Various Defuzzification Methods for Triangular Fuzzy Numbers Under a Fuzzy Inventory Model

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

A deterministic multi-item inventory model with quadratic demand under neutrosophic and pythagorean hesitant fuzzy programming approach

In this paper, a deterministic fuzzy inventory model with quadratic demand pattern, time-dependent holding cost, and time-dependent deterioration has been created. We have taken the rate of shortage as fully backlogged. In traditional inventory model, most of the cost parameters were taken as crisp. But in real world, fuzzy cost parameters are more realistic to appear instead of crisp parameters. Due to uncertainty we have considered all the cost parameters as hexagonal fuzzy number. We have regarded all of the cost parameters as hexagonal fuzzy numbers due to uncertainty. Our primary goal is to reduce the total average cost, and for that we've covered two optimization techniques: the Pythagorean Hesitant Fuzzy Programming Approach (PHFPA) and the Neutrosophic Hesitant Fuzzy Programming approach (NHFP).Through extensive numerical experiments and sensitivity analysis, the effectiveness and practicality of the proposed model are demonstrated. Comparative studies with traditional inventory models underscore the advantages of the Neutrosophic and Pythagorean Hesitant Fuzzy Programming Approach in managing multi-item inventory systems with quadratic demand patterns, highlighting its robustness in handling uncertain and ambiguous information.

Fuzzy Inventory Model with Eco Friendly Package, Carbon Emission, Cap Policy and Life Cycle Assessment Technology

Environmental sustainability has turn out to be more famous in recent years. It is to observe about environmental interactions to count on environmental declination. In addition, global warming is one of the major threats in our day to day lifestyles. Because of this global warming greenhouse gases takes place .GHG occurs particularly through human activities like combustion of fossil fuels in factories ,power plants etc. Also, it increases carbon emissions that absorb heat energy which is emitted from earth surface. Supply chain sustainability is affecting an employer deliver chain or logistics community and its far often related to an incorporating economic, social and environmental components .This paper investigates that the environmental pollutants to achieve sustainability , Green inventory model is used to achieve a minimum carbon emission using fuzzy logic. Fuzzy logic has been majorly used nowadays. It is applied to many fields, from control theory to artificial intelligence .Fuzzy logic is useful for minimizing the total cost, that is to reduce (GHG) emission through logistics activities.

Improve Fuzzy Inventory Model of Fractal Interpolation with Vertical Scaling Factor

The inventory model is used to determine the optimal inventory of a product. In certain cases, parameters in the inventory model are uncertain. Fractal interpolation techniques can be used to overcome parameter with uncertainty. Fractal interpolation results are affected by the fractal interpolation function and the vertical scaling factor. The vertical scaling factor is positive and less than 1. In this study, fractal interpolation techniques are introduced with variations in vertical scaling factor to overcome the uncertainty of demand data in inventory models. Furthermore, the interpolation results are used in fuzzy inventory models and expressed by Trapezoidal Fuzzy Number. This paper considers an inventory model with varying demand to optimize rice inventory. Based on the data obtained, the accuracy level will increase for the vertical scaling factor values close to 1. Optimal rice inventory of each successive fuzzy parameter is 1447963, 1013914, 504950, 215312. If the cost parameter is increased, then the amount of inventory is decreases.

A Two - Warehouse Fuzzy Inventory Model of Deteriorating Items under Exponentially Increasing Demand

A Two - Warehouse Fuzzy Inventory Model of Deteriorating Items under Exponentially Increasing Demand

Evaluation of the Effectiveness of Fuzzy Logic Sensitivity Analysis in Matlab Works for Evaluating the EOQ Production Inventory Model with Variable Demand with the Lagrangian and Kuhn-Tucker Methods

Abstract: To mirror the real world, the various inventory cost characteristics are also shown as interval numbers. The assumption is that the relationship between the product's demand and selling price is linearly descending. The supply chain has been optimized in this article using these two techniques with random demand. These two approaches have been compared, and a potential machine-learning strategy combining these two approaches has also been offered. The demand is thought to be random. Crisp and fuzzy models were utilized in this study to fix perishable products in the manufacturing process. The proposed model is solved using both the nonlinear mathematical Programming Lagrangian and Kuhn-tucker Methods. The Grade Mean Integration Representation technique is used to defuzzify data in the Fuzzy Inventory Model, which uses a Trapezoidal Fuzzy Number to determine the lowest prices. To support the solution process, a numerical example that includes sensitivity analysis is done at the end. Lagrangian, Kuhn-Tucker, and fuzzy logic analysis are used to analyze the Economic Order Quantity (EOQ) for changeable demand in this study. This research compares and contrasts their approaches, and the findings demonstrate the superiority of fuzzy logic over traditional approaches. To explore the price-dependent coefficients with variable demand and unit purchase cost over variable demand, trapezoidal fuzzy numbers are used in this research. The outcomes closely resemble the clean output. To validate the model, sensitivity analysis in Matlab was additionally carried out

Machine learning based fuzzy inventory model for imperfect deteriorating products with demand forecast and partial backlogging under green investment technology

This article proposes a novel approach to managing inventory by incorporating machine learning techniques to handle imperfect deteriorating products under green investment technology. The shortages are permitted and partially backlogged. Due to uncertainty, deterioration rate and defective percentage in quantity in the received lot are considered fuzzy variables. This study aims to determine optimal ordering quantity and replenishment period to minimise the total average cost with carbon emission cost. Decision Tree Classifier algorithm is used to demand forecast seasonally. The total fuzzy cost functions defuzzify by applying sign distance approach method. A numerical example is taken to illustrate the proposed model. A comparative analysis has been studied between fixed demand and month-wise forecasted demand. The study highlights the importance of forecasted demand in the inventory system and establishes methodology to get direct month-wise forecasted demand. Finally, the sensitivity analysis performs to determine more sensitive parameters and provides managerial insights.

Fuzzy Inventory Model of Deteriorating Items under Power Dependent Demand and Inventory Level Dependent Holding Cost Function

The present paper deals with the development of a fuzzy inventory model of deteriorating itemsunder power demand rate and inventory level dependent holding cost function. The deteriorationrate, demand rate, holding cost and unit cost are considered as trapezoidal fuzzy numbers. Both the crisp model and fuzzy model are developed in this paper. The graded mean integration method(GM) and signed distance method(SD) are used to defuzzify the total cost of the present model. Both the models are illustrated by suitable numerical examples and a sensitivity analysis for the optimal solution towards changes in the system parameters are discussed. Lastly a graphical presentation is furnished to compare the total costs under the above two mentioned methods in the fuzzy model.

Study on fuzzy inventory model for deteriorating items with recurring seasonal demand pattern

Study on fuzzy inventory model for deteriorating items with recurring seasonal demand pattern

Fuzzy Inventory Model for Imperfect Items with Price Discount and Penalty Maintenance Cost

The present paper considers the fuzzy economic manufacturing model (FEMM) for an inventory model with an imperfect production process that has been studied along with rework. During the pandemic, it is evident that the products accumulated without a sale, which has increased the maintenance cost of the products. This research paper compares a special sale of products with discount and without discount prices both in the fuzzy environment and in the crisp case. New computing methods based on fuzzy logic are being utilized to enhance identification, decision making, and optimization. A triangular fuzzy number is applied in the economic production quantity to emphasize the importance of optimal manufacturing. The EPQ model’s optimal total cost is obtained in the crisp version. It is to be noted that this model is developed in the fuzzy sense by using the deterioration as a triangular fuzzy number. The applications of this model in the fields are constructing customized industrial machinery or heavy‐duty construction equipment, specific chemicals, and processed food. By using MATLAB R2021, a numerical example of the optimal solution is provided. Finally, the present research discusses how changing several parameters affects the optimum total cost.

A fuzzy inventory model for Gompertz deteriorating items with cubic demand and shortages under the fully backlogged condition

A fuzzy inventory model for Gompertz deteriorating items with cubic demand and shortages under the fully backlogged condition

Extended Uncertainty Principle for Inventory Control: An Updated Review of Environments and Applications

This paper provides a comprehensive evaluation and categorization of the various uncertain environment employed by researchers and scientists to model and analyze inventory management systems in diverse sectors, including healthcare, supply chain, and routing issues. Additionally, it examines the challenges associated with the classical inventory model and introduces the concepts of fuzzy theory and the extended fuzzy principle in inventory management. The article presents important definitions related to fuzzy theory, including the fuzzy inventory model and its challenges. It also explores the applications of the extended fuzzy principle in real-life problems. The study focuses on inventory management under the extended fuzzy principle (Intuitionistic, Neutrosophic, Pythagorean, and so on), considering uncertain demand and imprecise data. The research contributes to the field by providing insights into the potential of fuzzy theory in overcoming the challenges of classical models and improving decision-making in inventory management.