Some Alternative Methods of Finding the Optimal Order Quantity in Inventory Models

2005 ◽  
Vol 57 (1-2) ◽  
pp. 121-128
Author(s):  
Ayan Chandra ◽  
S. P. Mukherjee
Keyword(s):  
Alternative Methods ◽  
Exceedance Probability ◽  
Optimal Order ◽  
Order Quantity ◽  
Inventory Problem ◽  
Inventory Models ◽  
Demand And Supply ◽  
Total Cost ◽  
Optimum Order ◽  
Optimal Order Quantity

We consider a purchase inventory problem where both demand and supply have been taken to be random. Several possible ways of deriving the optimum order quantity based on the distribution of total cost have been proposed. Expressions for the optimum order quantity that minimizes the mode or exceedance probability of this distribution have been worked out for some particular demand and supply distributions.

scholarly journals PENGENDALIAN PERSEDIAAN PROBABILISTIK PRODUK SUBSTITUSI DENGAN PERMINTAAN SEBAGAI FUNGSI HARGA

2021 ◽  
Vol 16 (1) ◽  
pp. 56-62
Author(s):  
Laila Nafisah ◽  
Sutrisno Sutrisno
Keyword(s):  
Sensitivity Analysis ◽  
Inventory Model ◽  
Optimal Order ◽  
Lost Sales ◽  
Business Unit ◽  
Order Quantity ◽  
Product Substitution ◽  
Inventory Models ◽  
Total Cost ◽  
Optimal Order Quantity

Kamara Living merupakan suatu unit usaha yang bergerak dalam penjualan kebutuhan sehari-hari. Salah satu produk yang populer adalah sarung bantal. Sarung bantal yang ditawarkan memiliki beberapa desain motif dan jenis yang berbeda. Permintaan akan produk sarung bantal tidak menentu antara satu desain dengan desain yang lain. Ketika desain tertentu persediaannya habis, perusahaan akan menawarkan desain lain dari jenis kain yang sama. Jika konsumen tidak bersedia maka terjadi kehilangan penjualan. Ketika persediaan berlebih, perusahaan akan memberikan harga promosi untuk mendongkrak tingkat penjualannya. Jika ini dibiarkan terus-menerus, tentu saja perusahaan akan mengalami penurunan keuntungan. Pada makalah ini dikembangkan model persediaan dengan mempertimbangkan produk substitusi dengan permintaan sebagai fungsi harga yang bertujuan untuk meminimasi total biaya persediaan. Penyelesaian model yang dilakukan mampu menghasilkan solusi kuantitas pemesanan dan titik pemesanan yang optimal. Validasi model dilakukan dengan membandingkan hasil dari model yang dikembangkan terhadap kondisi riil. Selain itu juga dilakukan analisis sensitivitas terhadap parameter-parameter yang berpengaruh. Abstract[Product-substitution Inventory Model with Demand depend on Price] Kamara Living is a business unit engaged in selling daily stuff. One popular product is pillowcases. The pillow cover offered has several different motif designs and types. The demand for pillowcases is uncertain between one design and another. When a stockout occurs for a particular design, the company will offer another design of the same type of fabric. If consumers are not willing, there will be lost sales. When there is overstock, the company will provide promotional prices to increase sales levels. If this is allowed to continue, of course the company will experience a decline in profits. In this paper, an inventory model is developed by considering substitute products with demand as a price function that aims to minimize the total cost of inventory. Completion of the model carried out is able to produce optimal order quantity and order point solutions. Model validation is done by comparing the results of the models developed against real conditions. In addition, a sensitivity analysis was carried out on the influential parameters.Keywords: Inventory Models; Product Substitution; Demand Depend on Price

An Optimal Inventory Policy for Items Having Constant Demand and Constant Deterioration Rate with Trade Credit

2012 ◽  
Vol 5 (2) ◽  
pp. 89-95 ◽  
Author(s):  
R. P. Tripathi ◽  
S. S. Misra
Keyword(s):  
Trade Credit ◽  
Optimal Order ◽  
Order Quantity ◽  
Inventory Models ◽  
Inventory Policy ◽  
Deterioration Rate ◽  
Optimal Order Quantity ◽  
Optimal Ordering ◽  
Constant Deterioration ◽  
Ordering Quantity

In most of the classical inventory models the demand is considered as constant. In this paper the model has been framed to study the items whose demand and deterioration both are constant. The authors developed a model to determine an optimal order quantity by using calculus technique of maxima and minima. Thus, it helps a retailer to decide its optimal ordering quantity under the constraints of constant deterioration rate and constant pattern of demand.

Optimal Order Quantity and Inventory Classification Using Clustering

2017 ◽  
Vol 4 (2) ◽  
pp. 41-52 ◽  
Author(s):  
Reshu Agarwal
Keyword(s):  
Inventory Management ◽  
Optimal Order ◽  
Order Quantity ◽  
Ordering Policy ◽  
Optimum Order ◽  
Frequent Items ◽  
Clustering Approach ◽  
Optimal Order Quantity ◽  
Data Objects ◽  
Research Studies

Clustering is the process of analyzing data to find clusters of data objects that are similar in some sense to one another. Some research studies have also extended the usage of clustering concept in inventory management. Yet, not many research studies have considered the application of clustering approach on determining both optimal order quantity and loss profit of frequent items. In this paper, ordering policy of frequent items in each cluster is determined and inventory is classified based on loss rule in each cluster. This helps inventory manager to determine optimum order quantity of frequent items together with the most profitable item in each cluster for optimal inventory control. An example is illustrated to validate the results.

scholarly journals ANALISIS PEMILIHAN SUPPLIER UNTUK PEMESANAN BAHAN BAKU YANG OPTIMAL MENGGUNAKAN METODE AHP DAN FUZZY AHP: STUDI KASUS DI PT XYZ

2013 ◽  
Vol 3 (3) ◽  
Author(s):  
Nunung Nurhasanah ◽  
Muhamad Aqil Tamam
Keyword(s):  
Wheat Flour ◽  
Fuzzy Ahp ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Optimal Order ◽  
Order Quantity ◽  
Total Cost ◽  
Optimal Order Quantity ◽  
Industry Needs ◽  
Hierarchy Process

<p>The availability of wheat flour as raw material is a crusial planning, especially for<br />PT. XYZ. That is why, this availability needs to be maintained, thus whenever industry needs<br />to produce noodle, wheat flour always available as stock.PT. XYZ has several suppliers to<br />supply wheat flour in present.But, in order to fulfill the supplies, PT. XYZ used to get their<br />lost because of the rejected and lateness of wheat flour as raw materials.In other way, this<br />company has not yet had a standard method to choose the best supplier.<br />This research has studied by using two methods in order to choose the best suppleirs.<br />These are Analitical Hierarchy Process (AHP) and Fuzzy AHP. This research has also<br />studied to fulfill the optimal raw material order. In order to get the optimal order quantity,<br />this research suggested Economic Order Quantity (EOQ) modeling.<br />This research has shown that there are no significant deferences between AHP and<br />Fuzzy AHP. Based on this research, PT. XYZ may use either AHP or Fuzzy AHP to choose<br />the best supplier. Based on EOQ, the optimal order quantity is 103.730kg, and company<br />should order every 23 days, meaning there is 16 times order to supplier. The reorder<br />point is 22.230kg, and the total cost is Rp.9.923.475.086.</p>

scholarly journals The Convergence of Gallego’s Iterative Method for Distribution-Free Inventory Models

Mathematics ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 484 ◽  
Author(s):  
Ting-Chen Hu ◽  
Kuo-Chen Hung ◽  
Kuo-Lung Yang
Keyword(s):  
Iterative Method ◽  
Optimal Solution ◽  
Threshold Value ◽  
Optimal Order ◽  
Order Quantity ◽  
Inventory Models ◽  
Worst Case ◽  
Distribution Free ◽  
Second Moments ◽  
Optimal Order Quantity

For inventory models with unknown distribution demand, during shortages, researchers used the first and the second moments to derive an upper bound for the worst case, that is the min-max distribution-free procedure for inventory models. They applied an iterative method to generate a sequence to obtain the optimal order quantity. A researcher developed a three-sequence proof for the convergence of the order quantity sequence. We directly provide proof for the original order quantity sequence. Under our proof, we can construct an increasing sequence and a decreasing sequence that both converge to the optimal order quantity such that we can obtain the optimal solution within the predesigned threshold value.

scholarly journals Analysis of Inventory Control by Using Economic Order Quantity Model – A Case Study in PT Semen Padang

2019 ◽  
Vol 18 (2) ◽  
pp. 116
Author(s):  
Prima Fithri ◽  
Alizar Hasan ◽  
Fadhita Maisa Asri
Keyword(s):  
Production Process ◽  
Inventory Control ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Optimal Order ◽  
Order Quantity ◽  
Cement Production ◽  
Total Cost ◽  
Optimal Order Quantity

Inventory control is a very important issue. It is because the amount of inventory will determine or affect the smoothness of the production process as well as the effectiveness and efficiency of the company. PT Semen Padang is a manufacturing company that produces 10,400,000 tons of cement per year. The achievement of the cement production target at this company depends on the availability of raw materials needed in the cement production process itself. Gypsum is an additional material of the cement production process which is very important because it is a raw material that must exist in the process of making cement. So, if the inventory of gypsum cannot meet the needs of production, then the production process of cement making will be disrupted. PT Semen Padang is using the Min-Max method for inventory control. But the costs are quite high. The cost of inventory can be minimized by using another method such as EOQ (Economic Order Quantity). The conclusions of this research are in 2016 by using EOQ method, the optimal order quantity is 32,073 ton per order, and the frequency is 9 times in a year with total cost Rp. 4,757,673,813.48, and in 2017, the optimal order quantity is 34,856 tons per order and the frequency is 9 times in a year with total cost Rp. 9,694,805,608.36.

scholarly journals Coping with Loss Aversion in the Newsvendor Model

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jianwu Sun ◽  
Xinsheng Xu
Keyword(s):  
Expected Utility ◽  
Loss Aversion ◽  
Confidence Level ◽  
Profit Maximization ◽  
Optimal Order ◽  
Market Demand ◽  
Newsvendor Model ◽  
Order Quantity ◽  
Decision Bias ◽  
Optimal Order Quantity

We introduce loss aversion into the decision framework of the newsvendor model. By introducing the loss aversion coefficientλ, we propose a novel utility function for the loss-averse newsvendor. First, we obtain the optimal order quantity to maximize the expected utility for the loss-averse newsvendor who is risk-neutral. It is found that this optimal order quantity is smaller than the expected profit maximization order quantity in the classical newsvendor model, which may help to explain the decision bias in the classical newsvendor model. Then, to reduce the risk which originates from the fluctuation in the market demand, we achieve the optimal order quantity to maximize CVaR about utility for the loss-averse newsvendor who is risk-averse. We find that this optimal order quantity is smaller than the optimal order quantity to maximize the expected utility above and is decreasing in the confidence levelα. Further, it is proved that the expected utility under this optimal order quantity is decreasing in the confidence levelα, which verifies that low risk implies low return. Finally, a numerical example is given to illustrate the obtained results and some management insights are suggested for the loss-averse newsvendor model.

scholarly journals Coordination of Supply Chain with One Supplier and Two Competing Risk-Averse Retailers under an Option Contract

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Rui Wang ◽  
Shiji Song ◽  
Cheng Wu
Keyword(s):  
Supply Chain ◽  
Conditional Value At Risk ◽  
Optimal Order ◽  
Pareto Optimum ◽  
Risk Averse ◽  
Order Quantity ◽  
Supply Chain System ◽  
Chain System ◽  
Option Contract ◽  
Optimal Order Quantity

This paper studies an option contract for coordinating a supply chain comprising one risk-neutral supplier and two risk-averse retailers engaged in promotion competition in the selling season. For a given option contract, in decentralized case, each risk-averse retailer decides the optimal order quantity and the promotion policy by maximizing the conditional value-at-risk of profit. Based on the retailers’ decision, the supplier derives the optimal production policy by maximizing expected profit. In centralized case, the optimal decision of the supply chain system is obtained. Based on the decentralized and centralized decision, we find the coordination conditions of the supply chain system, which can optimize the supply chain system profit and make the profits of the supply chain members achieve Pareto optimum. As for the subchain, we also find the coordination conditions, which generalize the results of the supply chain with one supplier and one retailer. Our analysis and numerical experiments show that there exists a unique Nash equilibrium between two retailers, and the optimal order quantity of each retailer increases (decreases) with its own (competitor’s) promotion level.

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