scholarly journals Inventory Level Improvement in Pharmacy Company Using Probabilistic EOQ Model and Two Echelon Inventory: A Case Study

2020 ◽  
Vol 13 (3) ◽  
pp. 229-242
Author(s):  
Desy Anisya Farmaciawaty ◽  
◽  
Mursyid Hasan Basri ◽  
Akbar Adhi Utama ◽  
Fransisca Budyanto Widjaja ◽  
...  
Keyword(s):  
Inventory Management ◽  
Lead Time ◽  
Inventory Level ◽  
Setup Cost ◽  
Inventory Cost ◽  
Decentralized System ◽  
Class A ◽  
Eoq Model ◽  
Holding Cost

Abstract. This research is aimed to maintain the inventory level in a two-echelon pharmacy company. The company is a pharmacy company that has 16 branches that operate in Bandung and the surrounding area. The company has a problem with its high inventory cost. To solve the problem, the authors compare two methods that suit the company condition, i.e., the decentralized system using probabilistic EOQ model and the centralization system using the multi-echelon inventory technique. We analyzed sales data and on-hand inventory data acquired from the company information system to perform the study. We limit the scope to the class A items only. We also assume the lead time, setup cost, and holding cost used in this study with the company's owner's consent. To conclude, using the decentralized system, the company will save 31% of their inventory cost, while using the centralization system with the multi-echelon technique, the company will be able to save 61% of their inventory cost. We recommend the company to refer to its competitive strategy before deciding which model it would be implemented. Keywords: Centralization, Decentralization, Probabilistic Economic Order Quantity (EOQ), Multi-Echelon Inventory, Pharmaceutical Inventory Management

EOQ Model with Controllable Lead Time, Setup Cost and Backordering Rate

2011 ◽  
Vol 204-210 ◽  
pp. 464-469 ◽  
Author(s):  
Bo Huang ◽  
Wei Dong Meng ◽  
Yu Yu Li
Keyword(s):  
Lead Time ◽  
Optimal Solution ◽  
General Distribution ◽  
Inventory Level ◽  
Order Quantity ◽  
Setup Cost ◽  
Safety Stock ◽  
Total Cost ◽  
Eoq Model ◽  
Controllable Lead Time

This paper developed an EOQ model, in which the demand follows a general distribution, under the assumption that lead time can be shortened and setup cost can be reduced by added investment, and backorder rate depends on inventory level and price discount in the period of shortage. We proved the existence and uniqueness of optimal solution and proposed an algorithm searching for it. We find that order quantity, safety stock and inventory total cost can be normally reduced by shortening lead time and reducing setup cost, furthermore, backordering parameter and probability of shortage have a great impact on inventory total cost, so an enterprise should do its best to reduce probability of shortage, especially when backordering parameter is small.

scholarly journals Analysis Inventory Cost Jona Shop with EOQ Model

2021 ◽  
Vol 3 (1) ◽  
pp. 21-25
Author(s):  
Abigail Vania ◽  
Hanni Yolina
Keyword(s):  
Lead Time ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Inventory Cost ◽  
Valid Model ◽  
Inventory Costs ◽  
Eoq Model ◽  
Holding Cost

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%.

scholarly journals Inventory model for deteriorating items with negative exponential demand, probabilistic deterioration and fuzzy lead time under partial back logging

2020 ◽  
Vol 30 (3) ◽  
Author(s):  
Nabendu Sen ◽  
Sumit Saha
Keyword(s):  
Inventory Management ◽  
Lead Time ◽  
Probability Distributions ◽  
Optimal Strategies ◽  
Inventory Model ◽  
Deteriorating Items ◽  
Optimal Time ◽  
Inventory Cost ◽  
Total Inventory ◽  
Negative Exponential

The effect of lead time plays an important role in inventory management. It is also important to study the optimal strategies when the lead time is not precisely known to the decision makers. The aim of this paper is to examine the inventory model for deteriorating items with fuzzy lead time, negative exponential demand, and partially backlogged shortages. This model is unique in its nature due to probabilistic deterioration along with fuzzy lead time. The fuzzy lead time is assumed to be triangular, parabolic, trapezoidal numbers and the graded mean integration representation method is used for the defuzzification purpose. Moreover, three different types of probability distributions, namely uniform, triangular and Beta are used for rate of deterioration to find optimal time and associated total inventory cost. The developed model is validated numerically and values of optimal time and total inventory cost are given in tabular form, corresponding to different probability distribution and fuzzy lead-time. The sensitivity analysis is performed on variation of key parameters to observe its effect on the developed model. Graphical representations are also given in support of derived optimal inventory cost vs. time.

Development of an EOQ Model for Single Source to Multi Destination

2012 ◽  
Vol 3 (4) ◽  
pp. 51-70
Author(s):  
Kanika Gandhi ◽  
P. C. Jha ◽  
M. Mathirajan
Keyword(s):  
Real Life ◽  
Fuzzy Optimization ◽  
Single Source ◽  
Short Life ◽  
Eoq Model ◽  
Industry Environment ◽  
Constant Quantity ◽  
Demand Rate ◽  
Holding Cost

Industry environment has become competitive because of product’s short life cycle. Competition reaches to extreme, when products are deteriorating which further makes demand uncertain. Generally, in deriving the solution of economic order quantity (EOQ) inventory model, the authors consider the demand rate as constant quantity. But in real life, demand cannot be forecasted precisely which causes fuzziness in related constraints and cost functions. Managing inventory, procurement, and transportation of deteriorating natured products with fuzzy demand, and holding cost at source and destination becomes very crucial in supply chain management (SCM). The objective of the current research is to develop a fuzzy optimization model for minimizing cost of holding, procurement, and transportation of goods from single source point to multi demand points with discount policies at the time of ordering and transporting goods in bulk quantity. A real life case study is produced to validate the model.

scholarly journals SUPPLY LEAD TIME UNCERTAINTY IN A SUSTAINABLE ORDER QUANTITY INVENTORY MODEL

2013 ◽  
Vol 4 (4) ◽  
pp. 15-27 ◽  
Author(s):  
Salvatore Digiesi ◽  
Giorgio Mossa ◽  
Giovanni Mummolo
Keyword(s):  
Inventory Management ◽  
Lead Time ◽  
Expected Value ◽  
Air Pollutant ◽  
Pollutant Emission ◽  
Optimal Order ◽  
Inventory Level ◽  
Order Quantity ◽  
Industrial Case Study ◽  
Safety Stock

Abstract Transport plays a key role in inventory management since it affects logistic costs as well as environmental performance of the supply chain. Expected value and variability of supply lead time depend on the transportation means adopted, and influence the optimal values of order quantity, reorder level, and safety stock to be adopted. Fast transportation means allow reducing expected value of the lead time; they are characterized by the highest costs of externalities (i.e. air pollutant emission, noise, congestion, accidents). On the contrary, slow transportation means require high inventory level due to large order quantity; in this case costs of externalities tend to decrease. The Sustainable Order Quantity (SOQ) [1] allows identifying optimal order quantity, reorder level, safety stock as well as transportation means which minimize the sum of the logistic and environmental costs in case of stochastic variability of product demand. In this paper, the authors propose a new SOQ analytical model considering stochastic variability of supply lead time (LT). A solution procedure is suggested for solving the proposed model. The approach is applied to a real industrial case study in order to evaluate the benefits of applying it if compared with the traditional one.

Comparative multi criteria analysis and dependent optimisation through integrated supply chain

2014 ◽  
Vol 63 (8) ◽  
pp. 1046-1069 ◽  
Author(s):  
Sanjay Sharma ◽  
Akshat Sisodia
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Service Level ◽  
Inventory Level ◽  
Inventory Policies ◽  
Inventory Cost ◽  
Content Type ◽  
Customer Service Level ◽  
Integrated Supply Chain ◽  
Different Levels

Purpose – The purpose of this paper is to compare various inventory policies and their effect on various performance metrics at different levels of a multi stage supply chain. Later the model is integrated to include optimization of entire supply chain through implementation of collaborative supply chain model. Design/methodology/approach – Alternative inventory policies have been developed at different echelons and a comparison reflecting the usability on various factors such as inventory level, inventory cost and service level is presented so as to support the decision-making process. Various inventory policies such as economic order quantity, periodic ordering (T, M) and stock to demand have been considered. Along with the basic assumptions; lead time, demand variability, variability in demand during lead time, stock out costs have also been included to make the model more applicable to practical situations. Findings – After the selection of most appropriate inventory policy at each level through a decision matrix, the total cost of operating such a supply chain is calculated along with other parameters such as service level and inventory turns. The approach is of aggregating the optimized value at each echelon referred to as aggregated supply chain in the paper. Then the concept of integrated supply chain is introduced which optimizes the supply chain as a whole, rather than aggregating local optima. The comparison is made between the two approaches that prove the integrated supply chain's superiority. Furthermore, dependent optimization is run as it is not practically possible for each echelon to optimize at the same time. Originality/value – Each echelon is allowed to optimize at a time and other echelons assume corresponding values. This final comparative multi criterion analysis is based on the three factors, i.e. inventory cost, customer service level and inventory turnover with different weights assigned to each factor at different levels of a supply chain. Finally a consolidation of results is made to reflect the overall preference which proves that an integrated supply chain best serves all the parameters combined together.

The Study of MTO Online Manufacturers' Guaranteed Delivery Time Model with Order Batching

2014 ◽  
Vol 933 ◽  
pp. 824-829
Author(s):  
Qiang Gang Zhu ◽  
Lei Liu ◽  
Yun Sheng Wang
Keyword(s):  
Lead Time ◽  
Delivery Time ◽  
Lot Size ◽  
Setup Cost ◽  
Time Model ◽  
Holding Cost ◽  
Inventory Holding Cost ◽  
Inventory Holding ◽  
Cost Of Transportation ◽  
Marketing Approach

To MTO on-line manufacturers, one of the most popular time-based competitive strategies is to widely advertise a uniform delivery time guarantee to all the customers. While providing time guarantee can be an effective marketing approach, it is critical for firms to reduce lead time to keep the promise. Decreasing lot size in batching is one of the most important levers to compress lead time in operation. This research expands existing blanket delivery-time guarantee models by integrating operation approach and marketing approach. The online manufacturers guaranteed delivery time model with order batching is established. Some analytic results are provided, and numerical examples are conducted to provide further insight into the problem. The effects of batch processing setup cost, unit inventory holding cost and unit compression cost of transportation time are analyzed. The results indicate that when batch processing setup cost decrease, unit inventory holding cost or unit compression cost of transportation time increase, the online manufacturer should decrease the lot size and shorten the guaranteed delivery time. The customers time and price sensitivities have adverse influences on the manufacturers delivery time decision.

scholarly journals An Algorithm for Solution of an Interval Valued EOQ Model

2012 ◽  
Vol 3 (1) ◽  
pp. 55-64 ◽  
Author(s):  
Susovan CHAKRABORTTY ◽  
Madhumangal PAL ◽  
Prasun Kumar NAYAK
Keyword(s):  
Lead Time ◽  
Solution Procedure ◽  
Lot Size ◽  
Setup Cost ◽  
Single Product ◽  
Interval Numbers ◽  
Eoq Model ◽  
Interval Valued ◽  
Total Average Cost ◽  
Total Average

This paper deals with the problem of determining the economic order quantity (EOQ)in the interval sense. A purchasing inventory model with shortages and lead time, whose carryingcost, shortage cost, setup cost, demand quantity and lead time are considered as interval numbers,instead of real numbers. First, a brief survey of the existing works on comparing and ranking anytwo interval numbers on the real line is presented. A common algorithm for the optimum productionquantity (Economic lot-size) per cycle of a single product (so as to minimize the total average cost) isdeveloped which works well on interval number optimization under consideration. A numerical exampleis presented for better understanding the solution procedure. Finally a sensitive analysis of the optimalsolution with respect to the parameters of the model is examined.

A FLUID EOQ MODEL WITH A TWO-STATE RANDOM ENVIRONMENT

2006 ◽  
Vol 20 (2) ◽  
pp. 329-349 ◽  
Author(s):  
Oded Berman ◽  
David Perry ◽  
Wolfgang Stadje
Keyword(s):  
Random Environment ◽  
Classical Problem ◽  
Type Model ◽  
Expected Number ◽  
Setup Cost ◽  
Eoq Model ◽  
Demand Rate ◽  
Markovian Random Environment ◽  
Holding Cost ◽  
Stochastic Fluid

We study a stochastic fluid EOQ-type model operating in a Markovian random environment of alternating good and bad periods determining the demand rate. We deal with the classical problem of “when to place an order” and “how big it should be,” leading to the trade-off between the setup cost and the holding cost. The key functionals are the steady-state mean of the content level, the expected cycle length (which is the time between two large orders), and the expected number of orders in a cycle. These performance measures are derived in closed form by using the level crossing approach in an intricate way. We also present numerical examples and carry out a sensitivity analysis.

scholarly journals Inventory Model with Demand Dependent on Unit Price under Fuzzy Parameters and Decision Variables

2019 ◽  
Vol 8 (3) ◽  
pp. 784-788
Keyword(s):  
Numerical Solutions ◽  
Unit Cost ◽  
Optimal Solution ◽  
Unit Price ◽  
Lot Size ◽  
Setup Cost ◽  
Eoq Model ◽  
Decision Variables ◽  
Holding Cost ◽  
Cost Parameters

An EOQ model with demand dependent on unit price is considered and a new approach of finding optimal demand value is done from the optimal unit cost price after defuzzification. Here the cost parameters like setup cost, holding cost and shortage cost and also the decision variables like unit price, lot size and the maximum inventory are taken under fuzzy environment. Triangular fuzzy numbers are used to fuzzify these input parameters and unknown variables. For the proposed model an optimal solution has been determined using Karush Kuhn-Tucker conditions method. Graded Mean Integration (GMI) method is used for defuzzification. Numerical solutions are obtained and sensitivity analysis is done for the chosen model

Sign in / Sign up

Export Citation Format

Share Document