Learning EOQ Model with Trade-Credit Financing Policy for Imperfect Quality Items under Cloudy Fuzzy Environment

An imprecise demand rate creates problems in profit optimization in business scenarios. The aim is to nullify the imprecise nature of the demand rate with the help of the cloudy fuzzy method. Traditionally, all items in an ordered lot are presumed to be of good quality. However, the delivered lot may contain some defective items, which may occur during production or maintenance. Inspection of an ordered lot is indispensable in most organizations and can be treated as a type of learning. The learning demonstration, a statistical development expressing declining cost, is necessary to achieve any cyclical process. Further, defective items are sold immediately after the screening process as a single lot at a discounted price, and the fraction of defective items follows an S-shaped learning curve. The trade-credit policy is adequate for suppliers and retailers to maximize their profit during business. In this paper, an inventory model is developed with learning and trade-credit policy under the cloudy fuzzy environment where the demand rate is treated as a cloudy fuzzy number. Finally, the retailer’s total profit is maximized with respect to order quantity. Sensitivity analysis is presented to estimate the robustness of the model.

An EOQ model for deteriorating items analyzing retailer’s optimal strategy under trade credit and return policy with nonlinear demand and resalable returns

This paper presents an EOQ model where demand is dependent upon time and selling price. In the proposed model of inventory, the retailer allows its unsatisfied customers to return their product whereas the manufacturer offers a full trade credit policy to the retailer. To make our model realistic, we have assumed that the product returned can be resold with the same selling price. Number of returns is a function of demand. In this proposed inventory model considering deterioration, the retailer does not fully reimburse its customers for the returned product. The primary purpose of this inventory model is to determine the optimal selling price, optimal order quantity, and optimal replenishment cycle length in order to maximize the retailer’s total profit earned per unit time. A numerical example is also presented and a sensitivity analysis is carried to highlight the findings of the suggested inventory model.

Inventory models with stock - and price-dependent demand for deteriotating items based on limited space

This paper deals with the problem of determining the optimal selling price and order quantity simultaneously under EOQ model for deteriorating items. It is assumed that the demand rate depends not only on the on-display stock level but also the selling price per unit, as well as the amount of shelf/display space is limited. We formulate two types of mathematical models to manifest the extended EOQ models for maximizing profits and derive the algorithms to find the optimal solution. Numerical examples are presented to illustrate the models developed and sensitivity analysis is reported.

An Optimized System to Reduce Procurement Risks and Stock-Outs: A Simulation Case Study for a Component Manufacturer

In the current global system; supply chains are at risk due to increasing procurement shortages, supply disruptions, and the reliability of on-time deliveries with the original order quantities. As a result, an anticipated management model is of vital importance to provide companies with the productive flexibility necessary to adapt quickly to supply changes, in order to ensure the quality and delivery time through efficient management of stocks and supply costs. In this context, this research aims to develop a system to complement classical procurement planning based on inventory management methods and MRP (material requirements planning) systems by considering suppliers’ behavior regarding procurement risks. For this purpose, a system is developed that seeks to simulate the impacts of procurement shortages of different natures. Moreover, the research investigates the development of a system that performs procurement planning of a component manufacturer to determine the supply orders necessary to meet the master production schedule. The system is analyzed based on a set of indicators in the event that the supplier of a material needed for production does not supply on time or has short-term problems. Several scenarios are simulated, and the results are quantified by changing the procurement order quantities, which may or may not follow the economic order quantity (EOQ) model, and the potential procurement disruptions or shortages. The results show how the simulation and anticipation of potential suppliers’ procurement behavior concerning potential shortages and their probability are key for successful procurement within a joint strategy with classical procurement methods.

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.

Inventory Model with Fixed Shelf Life under Generalized Non-Increasing Demand

In this paper, we develop an economic order quantity (EOQ) model for fixed shelf-life items and a non-increasing demand. The objective of this model is to maximize the total profit. We find the criterion to decide (i) the interior maximum solution or (ii) the boundary maximum solution. Eight numerical examples are given to illustrate all possible scenarios of this generalized model. Our results identify a scenario for which the maximum profit is always negative. This is highly relevant for firms in the public sector operating at a financial loss.

A Study of an EOQ Model of Growing Items with Parabolic Dense Fuzzy Lock Demand Rate

In this article, the parabolic dense fuzzy set is defined, and its basic arithmetic operations are studied with graphical illustration. The lock set concept is incorporated in a parabolic dense fuzzy set. Then, it is applied to the problems of fishery culture via the modeling of an economic order quantity model. Here, the fingerlings are fed to reach the ideal size to fulfill the customer’s demand. The growth rate of the fingerlings is assumed as a linear function. After the sales of all fish, the pond is cleaned properly for a new cycle. Here, the model is solved in a crisp sense first. Then, we fuzzify the model considering the demand rate as a parabolic dense lock fuzzy number and obtain the result in a fuzzy environment. The main aim of our study was to find the quantity of the ordering items such that the total inventory cost gets a minimum value. Lastly, sensitivity analysis and graphical illustrations were added for better justification of our model.

ANALISIS PENGENDALIAN PERSEDIAAN PAKAN TERNAK SAPI PADA PT INDO PRIMA BEEF DI KABUPATEN LAMPUNG TENGAH

The purposes of this study are to analyze cost-efficient control of feed raw material inventory, anticipate shortages of supply, determine the correct time frame for reordering raw materials at the feedlot company PT Indo Prima Beef using the Economic Order Quantity (EOQ) mathematical model and determine the inventory value of raw materials with the First In First Out (FIFO) assessment model. Data collection was carried out in March-May 2020 using a case study method. The data used were primary data collected using questionnaires and secondary data from literature studies. The results showed that the inventory cost applied by PT Indo Prima Beef was different from the calculation of the EOQ model. According to EOQ analysis, the largest amount of safety stock is corn sugarcane as much as 139,725.95 kg, and the lowest amount is salt around 870.63 kg. The reorder point for PT Indo Prima Beef with the largest amount was dry onggok as much as 139,926 kg, while the lowest amount was 724.87 kg of salt. PT Indo Prima Beef uses a perpetual recording system with the First In First Out (FIFO) inventory valuation method with a total raw material inventory value of IDR2,129,685,820 in one year.Key words: EOQ,FIFO, inventory, supplies