Guides to Inventory Policy

Magee, John F.

doi:10.1007/978-1-4613-4379-0_8

Cited by 16 publications

(14 citation statements)

References 1 publication

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“…The first book that used z-transforms in a production and inventory control context appears to be Brown (1963). Magee (1956) incorporated two proportional controllers into a stationary OUT policy and, without giving details of its derivation, studies variance amplification. Deziel and Eilon (1967) used a variant of the OUT policy z-transforms and the 'sum of the squares' technique to study variance amplification.…”

Section: Literature Reviewmentioning

confidence: 43%

The myopic Order-Up-To policy with a proportional feedback controller

Chen

Disney

2007

International Journal of Production Research

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We develop a discrete control theory model of a myopic Order-Up-To (OUT) policy reacting to a stochastic demand pattern with Auto Regressive and Moving Average (ARMA) components. We show that the bullwhip effect arises with such a policy despite the fact that it is optimal when the ordering cost is linear. We then derive a set of z-transform transfer functions of a modified OUT policy that allows us to avoid the bullwhip problem by incorporating a proportional controller into the inventory position feedback loop. With this technique, the order variation can always be reduced to the same level as the demand variation. However, bullwhip-effect avoidance always comes at the cost of holding extra inventory. When the ordering cost is piece-wise linear and increasing, we compare the total cost per period under the two types of control policies: with and without bullwhip-effect reduction. Numerical examples reveal that the cost saving can be substantial if the order variance is reduced by using the proportional controller.

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Section: Literature Reviewmentioning

confidence: 43%

The myopic Order-Up-To policy with a proportional feedback controller

Chen

Disney

2007

International Journal of Production Research

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“…This phenomenon is repeatedly shown in industry operations [7,8,15,16], macroeconomic data [1,2,10,11,17,20], and simulations such as "beer games" [9,12,21]. The bullwhip effect results in huge extra operation costs for suppliers; in some cases reported to be as much as 25% [3,13,14].…”

Section: Background and Definitionsmentioning

confidence: 43%

“…Obviously E X 0 = 0. To prove (15), consider the realization of one additional round, which may be initiated by supplier k and concluded by supplier s(> k). By conditional expectation,…”

Section: B Proof For (15)mentioning

confidence: 99%

Counteracting the bullwhip effect with decentralized negotiations and advance demand information

Ouyang¹,

Daganzo²

2006

Physica A: Statistical Mechanics and its Applications

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“…As this lead time increases, so does the safety stock that has to be held, since that depends on the standard deviation of product demand over the lead time. An early discussion of this problem can be found in Magee (1956). Figure 5 shows cycle time in days for a particular synchronous production facility, as a function of the fraction of excess capacity.…”

Section: Manufacturing Capacity and Lead Timessupporting

confidence: 40%

The Marketing/Manufacturing Interface: Strategic Issues

Karmarkar¹,

Lele²

International Series in Quantitative Marketing

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Most firms separate the marketing and manufacturing functions into distinct organizational groups without fully considering the interactions and conflicts between the two functions. These interactions can have very significant costs for the firm, if they are not recognized. We discuss situations in which strategy and policy in the two areas are not synchronized. They include issues such as capacity decisions, shift policy, and location in manufacturing; price-promotion policy, forecasting and market intelligence in marketing. These topics are discussed in the context of case examples which illustrate problems that can arise when interactions are not recognized.

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Guides to Inventory Policy

Cited by 16 publications

References 1 publication

The myopic Order-Up-To policy with a proportional feedback controller

The myopic Order-Up-To policy with a proportional feedback controller

Counteracting the bullwhip effect with decentralized negotiations and advance demand information

The Marketing/Manufacturing Interface: Strategic Issues

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