scholarly journals Deterministic EOQ models for non linear time induced demand and different holding cost functions

2016 ◽  
Vol 12 (2) ◽  
pp. 5949-5959 ◽  
Author(s):  
Surbhi Aneja ◽  
R P Tripathi ◽  
D Singh
Keyword(s):  
Linear Function ◽  
Linear Time ◽  
Inventory Level ◽  
Holding Costs ◽  
Eoq Model ◽  
Eoq Models ◽  
Level Ii ◽  
Non Linear ◽  
Demand Rate ◽  
Holding Cost

This paper presents an Economic order quantity (EOQ) model for deteriorating items. The demand rate is non-linear function of time. In this paper two models have been derived for different holding costs (i) The holding cost is linear function of the on hand inventory level. (ii). A non-linear function of time for which the item is kept in the stock. Optimization is done for both the models and numerical examples are presented to check the feasibility of the optimal solutions. Sensitivity analysis is also presented with respect to the various parameters used in the numerical example.

A Fluid EOQ Model with Markovian Environment

2015 ◽  
Vol 52 (02) ◽  
pp. 473-489
Author(s):  
Yonit Barron
Keyword(s):  
Continuous Time ◽  
Inventory Level ◽  
Continuous Time Markov Chain ◽  
Holding Costs ◽  
Eoq Model ◽  
Long Run ◽  
Average Criterion ◽  
Production Inventory ◽  
Finite State ◽  
Cost Functionals

We consider a production-inventory model operating in a stochastic environment that is modulated by a finite state continuous-time Markov chain. When the inventory level reaches zero, an order is placed from an external supplier. The costs (purchasing and holding costs) are modulated by the state at the order epoch time. Applying a matrix analytic approach, fluid flow techniques, and martingales, we develop methods to obtain explicit equations for these cost functionals in the discounted case and under the long-run average criterion. Finally, we extend the model to allow backlogging.

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.

A Fluid EOQ Model with Markovian Environment

2015 ◽  
Vol 52 (02) ◽  
pp. 473-489 ◽  
Author(s):  
Yonit Barron
Keyword(s):  
Continuous Time ◽  
Inventory Level ◽  
Continuous Time Markov Chain ◽  
Holding Costs ◽  
Eoq Model ◽  
Long Run ◽  
Average Criterion ◽  
Production Inventory ◽  
Finite State ◽  
Cost Functionals

We consider a production-inventory model operating in a stochastic environment that is modulated by a finite state continuous-time Markov chain. When the inventory level reaches zero, an order is placed from an external supplier. The costs (purchasing and holding costs) are modulated by the state at the order epoch time. Applying a matrix analytic approach, fluid flow techniques, and martingales, we develop methods to obtain explicit equations for these cost functionals in the discounted case and under the long-run average criterion. Finally, we extend the model to allow backlogging.

On the EOQ model with inventory-level-dependent demand rate and random yield

1994 ◽  
Vol 16 (3) ◽  
pp. 167-176 ◽  
Author(s):  
Shaul K. Bar-Lev ◽  
Mahmut Parlar ◽  
David Perry
Keyword(s):  
Inventory Level ◽  
Random Yield ◽  
Eoq Model ◽  
Demand Rate ◽  
Dependent Demand Rate ◽  
Dependent Demand

scholarly journals A Fluid EOQ Model with Markovian Environment

2015 ◽  
Vol 52 (2) ◽  
pp. 473-489 ◽  
Author(s):  
Yonit Barron
Keyword(s):  
Continuous Time ◽  
Inventory Level ◽  
Continuous Time Markov Chain ◽  
Holding Costs ◽  
Eoq Model ◽  
Long Run ◽  
Average Criterion ◽  
Production Inventory ◽  
Finite State ◽  
Cost Functionals

We consider a production-inventory model operating in a stochastic environment that is modulated by a finite state continuous-time Markov chain. When the inventory level reaches zero, an order is placed from an external supplier. The costs (purchasing and holding costs) are modulated by the state at the order epoch time. Applying a matrix analytic approach, fluid flow techniques, and martingales, we develop methods to obtain explicit equations for these cost functionals in the discounted case and under the long-run average criterion. Finally, we extend the model to allow backlogging.

AN EOQ MODEL WITH CONTROLLABLE SELLING RATE

2008 ◽  
Vol 25 (02) ◽  
pp. 151-167 ◽  
Author(s):  
HORNG-JINH CHANG ◽  
PO-YU CHEN
Keyword(s):  
Distribution Function ◽  
Transaction Cost ◽  
Optimal Solution ◽  
Bivariate Distribution ◽  
Inventory Level ◽  
Selling Price ◽  
Eoq Model ◽  
Concrete Form ◽  
Demand Rate ◽  
Classical Economic

According to the marketing principle, a decision maker may control demand rate through selling price and the unit facility cost of promoting transaction. In fact, the upper bound of willing-to-pay price and the transaction cost probably depend upon the subjective judgment of individual consumer in purchasing merchandise. This study therefore attempts to construct a bivariate distribution function to simultaneously incorporate the willing-to-pay price and the transaction cost into the classical economic order quantity (EOQ) model. Through the manipulation of the constructed bivariate distribution function, the demand function faced by the supplier can be expressed as a concrete form. The proposed mathematical model mainly concerns how to determine the initial inventory level for each business cycle, so that the profit per unit time is maximized by means of the selling price and the unit-transaction cost to control the selling rate. Furthermore, the sensitivity analysis of optimal solution is performed and the implication of this extended inventory model is also discussed.

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.

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