Fuzzy Inventory Model with Single Item Under Constant Demand and Time Dependent Holding Cost

The objective of this model is to discuss the inventory model for constant  demand and time dependent holding cost. Mathematical model has been developed for determining the optimal order quantity, the optimal cycle time and optimal total inventory cost in fuzzy environment. For defuzzification, graded unit preference integration method is used. Numerical examples are given to validate the proposed model. Sensitivity analysis is carried out to analyze the effect of changes in the optimal solution with respect to change in various parameters

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

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

A Fuzzy Economic Order Quantity (EOQ) Model with Consideration of Quality Items, Inspection Errors and Sales Return

In this paper, we develop an economic order quantity model with imperfect quality, inspection errors and sales returns, where upon the arrival of order lot, 100% screening process is performed and the items of imperfect quality are sold as a single batch at a lessen price, prior to receiving the next shipment. The screening process to remove the defective items may involve two types of errors. In this article we extend the Khan et al. (2011) model by considering demand and defective rate in fuzzy sense and also sales return in our model. The objective is to determine the optimal order lot size to maximize the total profit. We use the signed distance, a ranking method for fuzzy numbers, to find the approximate of total profit per unit time in the fuzzy sense. The impact of fuzziness of fraction of defectives and demand rate on optimal solution is showed by numerical example

Evaluation of SCOR KPIs using a predictive MILP model under fuzzy parameters.

The Supply Chain Operations Reference (SCOR) model is a well-recognized process reference model in the supply chain management field. Based on the literature, there is no research work that proposes a method to estimate and predict SCOR key performance indicators (KPIs) of a company. The objective of this paper is to propose a methodology to assess the SCOR KPIs under uncertainties based on level 2 of the SCOR-Make process metric, including nine KPIs. The proposed methodology consists of predictive MILP models with fuzzy parameters and some algorithms to assess the KPIs related to agility. A case study of a bottled-water factory is conducted to demonstrate the application of the proposed methodology. From the fact that some parameters are fuzzy numbers, the obtained SCOR KPIs are fuzzy numbers, which provide more information than constant values. The findings indicate that the proposed methodology is capable of developing the relationship between the manufacturing parameters and the SCOR KPIs, which enable the effective prediction process especially when the manufacturing parameters are changed or improved

A Fuzzy Inventory System with Deteriorating Items under Supplier Credits Linked to Ordering Quantity

[[abstract]]The inventory problem associated with trade credit is a popular topic in which interest income and interest payments are important issues. Most studies related to trade credit assume that the interest rate is both fixed and predetermined. However, in the real market, many factors such as financial policy, monetary policy and inflation, may affect the interest rate. Moreover, within the environment of merchandise storage, some distinctive factors arise which ultimately affect the quality of products such as temperature, humidity, and storage equipment. Thus, the rate of interest charges, the rate of interest earned, and the deterioration rate in a real inventory problem may be fuzzy. In this paper, we deal with these three imprecise parameters in inventory modeling by utilizing the fuzzy set theory. We develop the fuzzy inventory model based on Chang et al.'s [1] model by fuzzifying the rate of interest charges, the rate of interest earned, and the deterioration rate into the triangular fuzzy number. Subsequently, we discuss how to determine the optimal ordering policy so that the total relevant inventory cost, in the fuzzy sense, is minimal. Furthermore, we show that Chang et al.'s [1] model (the crisp model) is a special case of our model (the fuzzy model). Finally, numerical examples are provided to illustrate these results.[[notice]]補正完畢[[journaltype]]國內[[incitationindex]]SCI[[incitationindex]]EI[[ispeerreviewed]]Y[[booktype]]紙本[[countrycodes]]TW

Fuzzy inventory model on various lead time demand using multi criteria classification approach: A literature review

Inventory cost has become one of the major contributions to enterprise inefficiency.To minimize total cost, an enterprise is urged to manage an effective and efficient inventory system.In this case, an appropriate inventory model is in need. This study aims to propose an optimal inventory model by examining ABC multi-criteria classification approach using FANP (Fuzzy Analytical Network Process) and TOPSIS (Technique of Order Preferences by Similarity to the Ideal Solution) method. This study proposed a continuous review inventory model