MODEL ECONOMIC ORDER QUANTITY (EOQ) DAN MODEL OPTIMISASI ROBUST DALAM PENENTUAN PERSEDIAAN ALAT SUNTIK (SPUIT)

Inventory management and transportation have been the principal areas of focus in industrial engineering and management for a long time. Inventory management attracts considerable attention in logistics and supply chain management today because new supply chain models have become more integrative and complex. New market forces have introduced many complex elements which affect the performance of the supply chain in general and inventory level in particular. Inventory decisions are high risk and high impact for supply chain management. Hence, this paper compiles all the derivations of classical deterministic lot size economic order quantity models and proposes a new method to verify the formula. Keyword: Inventory Management, Supply Chain Management (SCM), Economic Order Quantity (EOQ) I. INTRODUCTION At the very basic level any firm faces two main decisions concerning the management of inventory: When should new stock be ordered and in what quantities? With regard to the order quantity, that minimizes inventory related costs. The classical EOQ (economic order quantity) model remains the basic inventory model even when it is not applicable in real life business situations in most cases. In inventory related literature, the answer to the question of when to order is given with reference to the ROP (reorder point), and the point at which the replenishment order should be initiated so that the facility receives the inventory in time to maintain its target level of service. In the static and deterministic model, the ROP is the simple multiplication of the number of lead days and the daily demand. It means that every time the inventory falls to the ROP level, an order must be initiated. And the order quantity is given by the EOQ model which is based on cost minimization. Figure-1:~ A simple inventory model based on fixed demand and fixed lead time (1). The EOQ is the balance between order and holding costs attached with the inventory. The order cost is made up of fixed and variable costs, whereas the holding cost consist of costs of maintenance. The formula is: Q = √ (2CoD/Cc) Q is the order quantity per order, D is the demand per year Co is the fixed cost which the warehouse incurs every time it places an order Cc is the inventory carrying or holding cost per unit per year, and Notice that it highlights two important insights regarding the EOQ model. These are: 1. Optimum order size is a balance between the holding cost and the fixed order cost. 2. Total inventory cost is related with order size, but the relationship is not significant.

Jona Shop is located in Indonesia, Jakarta is currently having a problem. The problem is the shop’s owner thinks that the inventory costs are too big especially for a powdered drink which brand is “Nutrisari”. The author finishes an EOQ (Economic Order Quantity) model for minimize the inventory cost. EOQ model is an old model but a valid model which still used now. Even EOQ model is an old model, many researchers used EOQ model to minimize inventory cost until 50% or more than 50%. But the EOQ model has some assumptions and Jona Shop fulfilled all the assumptions in the EOQ model. The assumptions of EOQ model are demand is known and constant, the lead time is constant and known, only one product can be estimated, every order is accepted in one-time delivery and can be used right away, there is no backorder because run out stock, no discount, and the holding cost per year and the ordering cost per year are constant. The result of the EOQ model can save up to almost 90%.

The Economic Order Quantity (EOQ) model, proposed by Harris in 1913, is one of the most studied models for the inventory management. The model aims at identifying the optimal lot size minimizing the total inventory costs, typically only holding and ordering costs. Many researchers extended this model trying to adapt it to real-life situation by providing new mathematical models. The increasing attention paid to sustainable manufacturing led, in the last years, to include the external costs of logistics in the EOQ model. Starting from a literature review on the inventory management models, this chapter defines the new Sustainable Order Quantity (SOQ) model. In the model, the loss factor parameter quantifies the loss in energy per unitary load transported and unitary distance covered, univocally identifying the various transport means. The optimal order quantity is derived minimizing a logistic cost function that considers both economic and social-environmental costs. The model allows determining at the same time the reorder level, the safety stock as well as the optimal transport means.

The economic order quantity (EOQ) model has become an important instrument in inventory management to minimize costs by balancing ordering and holding costs. This study examines the alignment of the EOQ model with the principles of Maqasid Shari’a, including hifdzul din (protecting religion), hifdzul nafs (protecting the soul), hifdzul aql (protecting reason), hifdzul nasl (protecting descendants), and hifdzul maal (protecting property) and its relevance in the context of Islamic business. Qualitative data were collected through a literature review with a content analysis approach, then analyzed thematically to identify the relationship between EOQ characteristics and Maqasid Shari’a dimensions. The results of the study indicate that the EOQ model is in line with the five principles of Maqasid Shari’a, which include: 1) Hifdzul din: 2) Hifdzul nafs: 3) Hifdzul aql: 4) Hifdzul nasl: 5) Hifdzul maal: This study concludes that by integrating the EOQ model with Maqasid Shari’a, maslahah (common good) will be achieved in the form of economic efficiency and strengthening the ethical and social dimensions in business. The implications will encourage increased transparency, waste reduction, and environmental sustainability. These findings can be a conceptual basis for developing a holistic inventory management model following Islamic economics principles.

In this paper, economic order quantity (EOQ) models without shortages for single item and multi-items are presented. Here, the holding cost of the item is a continuous function of the order quantity. The costs involved in this model are imprecise in nature. The main contributions of this research are as follows: The proposed EOQ model is discussed in two cases by describing the model in an uncertain environment. In case-1, EOQ models with fuzzy parameters (like ordering cost, holding cost, and unit product cost) are considered. Here all the fuzzy parameters are represented by trapezoidal fuzzy numbers. The said EOQ model is carried out by using the signed-distance method. In case-2, EOQ models with interval parameters (like ordering cost, holding cost, unit product cost, and the total money investment for the quantities) are considered. This proposed model is solved by using interval linear programming problem (ILPP) technique based on the best and the worst optimum values of the objective function. Numerical examples are given to exemplify the proposed model and also the results of different models are compared.KeywordsEOQTrapezoidal fuzzy numberInterval numberSigned-distance methodInterval linear programming problem (ILPP)

The presence of retail businesses in Indonesia has many positive impacts on the community, especially in improving the economy. The existence of buying and selling transactions involving suppliers, retailers, and the community as consumers can play a role in improving the national economy. Retail can be called a bridge for suppliers and consumers to meet their needs. The diversity of consumer needs requires retailers to provide a variety of products from many suppliers. Efforts that need to be made by retail businesses in order to minimize costs incurred are by controlling inventory. To prevent excessive expenditure, the inventory control method used is to apply the Economic Order Quantity (EOQ) model. The EOQ model can provide the optimum total inventory cost by adjusting the frequency of orders placed over a period of time. After obtaining the total inventory cost, the calculation of safety stock, reorder point, and maximum capacity can also be applied so that the inventory costs incurred can be minimal.

Inventory management is crucial for companies to minimize unnecessary costs associated with overstocking or understocking items. Utilizing the economic order quantity (EOQ) to minimize total costs is a key decision in inventory management, particularly in achieving a sustainable supply chain. The classical EOQ formula is rarely applicable in practice. For example, suppliers may enforce a minimum order quantity (MOQ) that is much larger than the EOQ. Some conditions such as imperfect quality and growing items represent variants of EOQ. Moreover, some requirements, such as the reduction of CO2 emissions, can alter the formula. Moreover, disruptions in the supply chain, such as COVID-19, can affect the formula. This study investigates which requirements must be considered during the calculation of the EOQ. Based on a literature review, 18 requirements that could alter the EOQ formula were identified. The level of coverage for these requirements has been tracked in the literature. Research gaps were presented to be investigated in future research. The analysis revealed that, despite their importance, at least 11 requirements have seldom been explored in the literature. Among these, topics such as EOQ in Industry 4.0, practical EOQ, and resilient EOQ have been identified as promising areas for future research.

The company's operational activities often experience problems with warehouse inventory which often experience a shortage of inventory. This deficiency causes operational activities to stop. This study aims to analyze inventory control of outer tire and inner tube warehouses using the Economic Order Quantity (EOQ). The results of the study show that the frequency of ordering with the old method is 67 times with an average order of 4 pcs, whereas according to the EOQ method, the frequency of orders that should be made is 21 times with 13 pcs/order, while the frequency of ordering with the old method is 25 times with the average order is 12 pcs and according to the EOQ method, the order frequency is 36 times with a quantity per message of 8 pcs. Safety stock according to the EOQ method for outer tires is 1.6 pcs and for inner tubes is 1.4 pcs, while the method applied by the company does not carry out safety stock. Re-Order Point of the old method is when the stock is less than 3 pcs, whereas according to EOQ, Re-order when the stock is only 4.6 pcs and the inner tube is 4.4 pcs. The total cost of inventory for outer tire and inner tube warehouses in 2021 using the EOQ method is less than company policy. The total inventory cost from the EOQ method for the outer tires was Rp. 441,325.88 and for the inner tubes was Rp. 570,497.57, while for the outer tires was Rp. 8,949,666 and the inner tubes were Rp. 8,631,635. Abstrak Kegiatan operasional perusahaan sering mengalami permasalahan pada persediaan gudang yang sering mengalami kekurangan persediaan Kekurangan tersebut mengakibatkan kegiatan operasional terhenti. Penelitian ini bertujuan untuk menganalisa pengendalian persediaan barang gudang ban luar dan ban dalam dengan menggunakan Economic Order Quantity (EOQ). Hasil dari penelitian bahwa frekuensi pemesanan dengan metode lama adalah sebanyak 67 kali dengan rata-rata pemesanan 4 pcs, sedangkan menurut metode EOQ, frekuensi pemesanan yang seharusnya dilakukan adalah 21 kali dengan 13 pcs/order, sedangkan frekuensi pemesanan dengan metode lama adalah 25 kali dengan rata-rata pemesanan sebanyak 12 pcs dan menurut metode EOQ, frekuensi pemesanan adalah sebanyak 36 kali dengan kuantitas per pesan 8 pcs. Safety stock menurut metode EOQ untuk ban luar adalah sebesar 1,6 pcs dan ban dalam adalah sebesar 1,4 pcs, sedangkan metode yang diterapkan perusahaan tidak melakukan persediaan pengaman. Re-Order Point metode lama adalah ketika stock kurang dari 3 pcs, sedangkan menurut EOQ, Re-order ketika stock tinggal 4,6 pcs dan ban dalam 4,4 pcs. Total biaya persediaan pada barang gudang ban luar dan ban dalam tahun 2021 dari metode EOQ lebih kecil dibanding kebijakan perusahaan. Total biaya persediaan dari metode EOQ pada ban luar sebesar Rp 441.325,88 dan pada ban dalam sebesar Rp 570.497,57, sedangkan untuk ban luar adalah sebesar Rp 8.949.666 dan pada ban dalam adalah sebesar Rp 8.631.635.

Deterministic Economic Order Quantity (EOQ) models have been studied intensively in the literature, where the demand process is described by an ordinary differential equation, and the objective is to obtain an EOQ, which minimizes the total cost per unit time. The total cost per unit time consists of a “discrete” part, the setup cost, which is incurred at the time of ordering, and a “continuous” part, the holding cost, which is continuously accumulated over time. Quite formally, such deterministic EOQ models can be viewed as fluid approximations to the corresponding stochastic EOQ models, where the demand process is taken as a stochastic jump process. Suppose now an EOQ is obtained from a deterministic model. The question is how well does this quantity work in the corresponding stochastic model. In the present paper we justify a translation of EOQs obtained from deterministic models, under which the resulting order quantities are asymptotically optimal for the stochastic models, by showing that the difference between the performance measures and the optimal values converges to zero with respect to a scaling parameter. Moreover, we provide an estimate for the rate of convergence. The same issue regarding specific Economic Production Quantity (EPQ) models is studied, too.

The rise of consumer rights has caused businesses to focus increasingly on product quality. The inability of businesses to identify defective items before selling them results in higher return costs, decreased sales revenue, damaged reputations, and decreased competitiveness. This study examines the economic order quantity (EOQ) model in which the retailer discovers defective goods among received products. Although retailers conduct quality inspections, the inspection process is imperfect. We assume that Type I and Type II inspection errors occur during product quality inspection and that the market demand rate is sensitive to Type II inspection errors. To improve inspection, the retailer invests capital to decrease Type II inspection errors. This study investigates the optimal order quantity and the power of the test to maximize total profit per unit time. Mathematical analysis is used to show the optimal solution exists. An algorithm is then developed to calculate the optimal solution. Finally, numerical examples demonstrate the solution process and sensitivity analysis with respect to major parameters is carried out.

The effective supply chain scheduling is a crucial task in business management which can be determined by developing the optimum schedules. Here, this paper develops the optimum schedules using an EOQ model with dynamic demand pattern because in this era of globalization and dynamic environment the Economic Order Quantity (EOQ) model loses its importance when it is based upon the constant demand pattern. Therefore, it becomes indispensable to develop the EOQ model under an environment of dynamic demand pattern. Here, the dynamic demand pattern includes the relevant parameters which varies with time. The effects of such parameters are necessary to incorporate in determining the optimum schedules and hence the optimum inventory levels. Also, to establish a product in the market and to increase its customer base one can take the help of promotional efforts in the form of trade credit financing. This paper discusses the optimum scheduling for a part of supply chain system using an EOQ model where the demand is dynamic varies with time and one of the promotional effort in the form of a two-stage trade credit is considered. The applicability of the model can be well understood through the sensitivity analysis of the parameters and its managerial implications.

FAbstract - Furniture Tenang Jaya Is a business that is engaged in furniture. The raw material used is teak wood, in a smooth production process, the company must provide sufficient raw material so that they do not experience excess or lack of raw material. The research method used is descriptive quantitative data in the form of numbers, Data collection techniques used were interviews and documentation. Data analysis techniques used in this study are by step (1) Production data (2) Determine Lead time (3) Determine Safety Stock (4) Determine Re-order Point (5) Calculated the most economical amount of goods purchased using the Economic Method Order Quantity (6) Determine Total Cost (7) Determine maximum Stock Maximum Stock (8) Determine Order Frequency (9) Make a graphic image / curve to measure Safety Stock, Reorder Point (ROP), and Economic Order Quantity (EOQ) positions so the results of the analysis are clear. The result showed that in 2017 Lead Time was IDR 16.159.500. Safety Stock is IDR 17.955.000. Re-order Points as much as IDR 34.114.500. Economic Order Quantity 3.870. The booking IDR 9.250.000 and the storage IDR 7.770.000. IDR 17.958.870. maximal stock the order frequency is 5 times. In 2018 the lead time was Idr 19.563.600 Safety Stock was IDR 23.273.997. Re-orde Points as much as IDR 42.927.597. Economic Order Quantity 4.152 The booking Rp 10.000.000 and the storage Rp. 10.200.000. Maximal stock of IDR 23.278.149 The order frequency is 5 imes. By using the economic order quantity method in Tenang Jaya Furniture, it can streamline production costs. Keyword: Inventory Planning, Controlling Production Cost

The application of the Economic Order Quantity (EOQ) method in managing raw material supplies for Pempek Isti, a micro, small, and medium enterprise (MSME) specializing in Palembang's culinary specialty, Pempek. The study reveals that the current raw material supply management is inefficient, leading to frequent shortages or excess orders, resulting in additional costs and inefficiencies. To tackle this issue, the study proposes the implementation of the EOQ analysis to minimize inventory costs and maximize profits. The research focuses on determining the optimal order quantities for three key raw materials: ikan tenggiri, sago flour, and eggs. After conducting the EOQ analysis, the study identifies the optimal order quantities as 37kg for mackerel fish, 44kg for sago flour, and 7kg for eggs. Furthermore, the study calculates the reorder points for each raw material based on the EOQ method, resulting in 8.36kg for mackerel fish, 8.19kg for sago flour, and 3.23kg for eggs. By implementing the EOQ method, Pempek Isti MSME can accurately estimate the required quantities of raw materials for Pempek production throughout the year. The calculations consider safety stock and lead time, enabling the determination of reorder points and maximum order quantities for each raw material. This information serves as a valuable reference for effectively managing the MSME's raw material supply chain. Overall, the application of the EOQ method is crucial in ensuring an efficient supply chain for Pempek Isti MSME. By implementing proper planning, control, and supervision of raw materials, the company can minimize costs, prevent stockouts, and avoid excessive inventory. This study provides valuable insights into optimizing inventory management, particularly in the context of MSMEs operating in the culinary industry.

A computerized system to maximize inventory performance in a small hospital is described. An inventory control system, which integrates economic order quantity (EOQ) and ABC inventory models was implemented in a 146-bed hospital. The perpetual inventory control data base, supported by the hospital's mainframe computer, generates monthly inventory statistics that are segregated into A, B, and C reports. Using a hand-held computer that interfaces with the perpetual inventory system, a series of inventory management reports were developed. These reports, which are based on the EOQ model, provide the following information for each drug line item: EOQ, EOQ proposed carrying cost, actual inventory carrying costs, safety stock, order point, average inventory, and the "on hand/on order" point. Several supplemental inventory management reports were also developed. While implementing the computerized inventory system, the pharmacy also changed its purchasing strategy from predominantly direct accounts to a progressive prime-vendor wholesaler. From December 1980 to December 1981, the ABC/EOQ system with progressive prime-vendor involvement essentially doubled total aggregate inventory turnover. A 46.5% reduction in standing inventory levels occurred. The drug cost per line item dispersed remained relatively constant over the one-year period, despite price increases. The application of the computerized ABC/EOQ inventory model to an online perpetual inventory control data base effectively reduced the inventory operation costs.

In this study, under the carbon cap-and-trade mechanism, the ordering cost presents a stepwise function for ordering quantity, and the optimal economic ordering quantity model aims to explore the manufacturer's total cost minimization in the finite planning horizon, in combination with the actual situation that the product will produce carbon emissions during transportation and storage. The economic order quantity (EOQ) model with stepwise ordering cost is applicable to the decision environment in which goods are utilized by sea, by rail or by air (e.g., the order cost is charged in addition to the basic fixed cost, the importer of raw materials will pay an additional freight related to delivery, such as the rent for the use of container numbers.). A heuristic algorithm is also proposed to analyze the relevant properties of the optimal solution of the model and to solve the optimal order times and quantities of the manufacturer under the constraint of carbon policy.We further compared the optimal order times with the case without carbon constraint and the order times corresponding to the manufacturer's realization of the minimum carbon emission, and obtained the conditions for the manufacturer to achieve low cost and low emission under the carbon policy.Finally, the theoretical results of the model are verified by numerical examples,and the influence of relevant parameters on the inventory strategy of manufacturers is discussed. The results show that under the carbon cap-and-trade policy, there is an optimal ordering strategy that minimizes the total cost of the manufacturer in the finite horizon. When the demand of the manufacturer is under finite horizon and the carbon policy is equal to the specific multiplier of orders, the manufacturer can achieve a win-win result of low cost and low emissions.