Fight Inventory Shrinkage: Simultaneous Learning of Inventory Level and Shrinkage Rate

2021 ◽  
Author(s):  
Rong Li ◽  
Jing-Sheng Jeannette Song ◽  
Shuxiao Sun ◽  
Xiaona Zheng
Keyword(s):  
Shrinkage Rate ◽  
Inventory Level ◽  
Inventory Shrinkage

scholarly journals Optimal Ordering Policy of a Risk-Averse Retailer Subject to Inventory Inaccuracy

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Lijing Zhu ◽  
Ki-Sung Hong ◽  
Chulung Lee
Keyword(s):  
Risk Aversion ◽  
Customer Service ◽  
Value At Risk ◽  
Conditional Value At Risk ◽  
Inventory Level ◽  
Risk Averse ◽  
Ordering Policy ◽  
Radiofrequency Identification ◽  
Optimal Ordering Policy ◽  
Inventory Shrinkage

Inventory inaccuracy refers to the discrepancy between the actual inventory and the recorded inventory information. Inventory inaccuracy is prevalent in retail stores. It may result in a higher inventory level or poor customer service. Earlier studies of inventory inaccuracy have traditionally assumed risk-neutral retailers whose objective is to maximize expected profits. We investigate a risk-averse retailer within a newsvendor framework. The risk aversion attitude is measured by conditional-value-at-risk (CVaR). We consider inventory inaccuracy stemming both from permanent shrinkage and temporary shrinkage. Two scenarios of reducing inventory shrinkage are presented. In the first scenario, the retailer conducts physical inventory audits to identify the discrepancy. In the second scenario, the retailer deploys an automatic tracking technology, radiofrequency identification (RFID), to reduce inventory shrinkage. With the CVaR criterion, we propose optimal policies for the two scenarios. We show monotonicity between the retailer’s ordering policy and his risk aversion degree. A numerical analysis provides managerial insights for risk-averse retailers considering investing in RFID technology.

Determination of Optimal Reserve between Two Machines in Series with the Repair Time has Change of Distribution after the Truncation Point

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 577-585
Author(s):  
T. Vivekanandan ◽  
S. Sachithanantham
Keyword(s):  
Real Life ◽  
Random Variable ◽  
Repair Time ◽  
Inventory Level ◽  
Optimal Size ◽  
Truncation Point ◽  
In Series ◽  
Optimal Reserve ◽  
Optimal Inventory Level ◽  
Two Machines

In inventory control, suitable models for various real life systems are constructed with the objective of determining the optimal inventory level.  A new type of inventory model using the so-called change of distribution property is analyzed in this paper. There are two machines M1 and M2  in series and the output of M1 is the input of M2. Hence a reserve inventory between M1 and M2 is to be maintained. The method of obtaining the optimal size of reserve inventory, assuming cost of excess inventory, cost of shortage and when the rate of consumption of M2  is a constant, has already been attempted.  In this paper, it is assumed that the repair time of M1  is a random variable and the distribution of the same undergoes a change of distribution  after the truncation point X0 , which is taken to be a random variable.  The optimal size of the reserve inventory is obtained under the above said  assumption . Numerical illustrations are also provided.

Approximations for the single-product production-inventory problem with compound Poisson demand and service-level constraints

1984 ◽  
Vol 16 (2) ◽  
pp. 378-401 ◽  
Author(s):  
A. G. De kok ◽  
H. C. Tijms ◽  
F. A. Van der Duyn Schouten
Keyword(s):  
Poisson Process ◽  
Compound Poisson Process ◽  
Service Level ◽  
Inventory Level ◽  
Inventory Problem ◽  
Single Product ◽  
Compound Poisson ◽  
Poisson Demand ◽  
Production Inventory ◽  
Random Fluctuations

We consider a production-inventory problem in which the production rate can be continuously controlled in order to cope with random fluctuations in the demand. The demand process for a single product is a compound Poisson process. Excess demand is backlogged. Two production rates are available and the inventory level is continuously controlled by a switch-over rule characterized by two critical numbers. In accordance with common practice, we consider service measures such as the average number of stockouts per unit time and the fraction of demand to be met directly from stock on hand. The purpose of the paper is to derive practically useful approximations for the switch-over levels of the control rule such that a pre-specified value of the service level is achieved.

A Novel Method to Determine the Drilling Fluid Density for Gypsum-Salt Layer

2021 ◽  
Author(s):  
Jitong Liu ◽  
Wanjun Li ◽  
Haiqiu Zhou ◽  
Yixin Gu ◽  
Fuhua Jiang ◽  
...  
Keyword(s):  
Drilling Fluid ◽  
In Situ Stress ◽  
Wellbore Stability ◽  
Shrinkage Rate ◽  
Fluid Density ◽  
Salt Layer ◽  
Rock Creep ◽  
Key Factor ◽  
Well Abandonment

Abstract The reservoir underneath the salt bed usually has high formation pressure and large production rate. However, downhole complexities such as wellbore shrinkage, stuck pipe, casing deformation and brine crystallization prone to occur in the drilling and completion of the salt bed. The drilling safety is affected and may lead to the failure of drilling to the target reservoir. The drilling fluid density is the key factor to maintain the salt bed’s wellbore stability. The in-situ stress of the composite salt bed (gypsum-salt -gypsum-salt-gypsum) is usually uneven distributed. Creep deformation and wellbore shrinkage affect each other within layers. The wellbore stability is difficult to maintain. Limited theorical reference existed for drilling fluid density selection to mitigate the borehole shrinkage in the composite gypsum-salt layers. This paper established a composite gypsum-salt model based on the rock mechanism and experiments, and a safe-drilling density selection layout is formed to solve the borehole shrinkage problem. This study provides fundamental basis for drilling fluid density selection for gypsum-salt layers. The experiment results show that, with the same drilling fluid density, the borehole shrinkage rate of the minimum horizontal in-situ stress azimuth is higher than that of the maximum horizontal in-situ stress azimuth. However, the borehole shrinkage rate of the gypsum layer is higher than salt layer. The hydration expansion of the gypsum is the dominant reason for the shrinkage of the composite salt-gypsum layer. In order to mitigate the borehole diameter reduction, the drilling fluid density is determined that can lower the creep rate less than 0.001, as a result, the borehole shrinkage of salt-gypsum layer is slowed. At the same time, it is necessary to improve the salinity, filter loss and plugging ability of the drilling fluid to inhibit the creep of the soft shale formation. The research results provide technical support for the safe drilling of composite salt-gypsum layers. This achievement has been applied to 135 wells in the Amu Darya, which completely solved the of wellbore shrinkage problem caused by salt rock creep. Complexities such as stuck string and well abandonment due to high-pressure brine crystallization are eliminated. The drilling cycle is shortened by 21% and the drilling costs is reduced by 15%.

Multi-objective particle swarm optimisation approach for production-inventory control systems

2018 ◽  
Vol 13 (4) ◽  
pp. 1037-1056 ◽  
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo
Keyword(s):  
Control System ◽  
Control Systems ◽  
Inventory Control ◽  
Dynamic Performance ◽  
Particle Swarm ◽  
Particle Swarm Optimisation ◽  
Inventory Level ◽  
Content Type ◽  
Multi Objective ◽  
Production Inventory

Purpose This paper aims to optimise the dynamic performance of production–inventory control systems in terms of minimisation variance ratio between the order rate and the consumption, and minimisation the integral of absolute error between the actual and the target level of inventory by incorporating the Pareto optimality into particle swarm optimisation (PSO). Design/method/approach The production–inventory control system is modelled and optimised via control theory and simulations. The dynamics of a production–inventory control system are modelled through continuous time differential equations and Laplace transformations. The simulation design is conducted by using the state–space model of the system. The results of multi-objective particle swarm optimisation (MOPSO) are compared with published results obtained from weighted genetic algorithm (WGA) optimisation. Findings The results obtained from the MOPSO optimisation process ensure that the performance is systematically better than the WGA in terms of reducing the order variability (bullwhip effect) and improving the inventory responsiveness (customer service level) under the same operational conditions. Research limitations/implications This research is limited to optimising the dynamics of a single product, single-retailer single-manufacturer process with zero desired inventory level. Originality/value PSO is widely used and popular in many industrial applications. This research shows a unique application of PSO in optimising the dynamic performance of production–inventory control systems.

scholarly journals Postponement Application in the Fast Fashion Supply Chain: A Review

2017 ◽  
Vol 12 (7) ◽  
pp. 115 ◽  
Author(s):  
MdAfzalul Aftab ◽  
Qin Yuanjian ◽  
Nadia Kabir
Keyword(s):  
Supply Chain ◽  
Value Chain ◽  
Building Blocks ◽  
Inventory Level ◽  
Successful Implementation ◽  
Process Standardization ◽  
Fast Fashion ◽  
Supply Chain Strategy ◽  
Manufacturing Operations ◽  
Inventory Holding

The successful implementation of push-pull supply chain management strategy has an important role in improving the competitiveness of an organization. The objective of a push-pull strategy is to minimize the holding of inventory level in finished form and rather produce finished goods from semi-finished inventory only upon receiving final order. One of the vital building blocks of push-pull supply chain strategy is postponement. The main objective of this review paper is to discuss the concept of postponement and its sub-categories such as product postponement and process postponement and their benefits. Then it is investigated how two prominent fast fashion retailers who are also categorized as original brand manufacturers in the apparel value chain apply the two variants of process postponement e.g. process standardization and process re-sequencing in their manufacturing operations to activate push pull supply chain strategy. The push-pull supply chain strategy in turn helps to reduce their order-to-delivery lead time to stores, reduce inventory holding level and minimize both physical costs and market mediation costs. The paper ends with concluding remarks. A framework is developed to illustrate the push-pull supply mechanism. This paper is a useful resource for practitioners in apparel supply chain willing to remove inefficiencies, costs and risks in their operations.

The impact of pre-employment integrity testing on employee turnover and inventory shrinkage losses

1987 ◽  
Vol 2 (2) ◽  
pp. 136-149 ◽  
Author(s):  
Thomas S. Brown ◽  
John W. Jones ◽  
William Terris ◽  
Brian D. Steffy
Keyword(s):  
Employee Turnover ◽  
Integrity Testing ◽  
Inventory Shrinkage ◽  
The Impact

scholarly journals Filtering and predicting the cost of hidden perished items in an inventory model

2002 ◽  
Vol 15 (3) ◽  
pp. 235-245
Author(s):  
Lakhdar Aggoun ◽  
Lakdere Benkherouf
Keyword(s):  
Joint Distribution ◽  
Inventory Model ◽  
The State ◽  
Inventory Level ◽  
Discrete State ◽  
History Of ◽  
Accumulated Losses ◽  
The Cost ◽  
State Of The Environment ◽  
Recursive Estimators

This paper is concerned with a discrete time, discrete state inventory model for items of changing quality. Items are assumed to be in one of a finite number, M, of quality classes that are ordered in such a way that Class 1 contains the best quality and the last class contains the pre-perishable quality. The changes of items' quality are dependent on the state of the ambient environment. Furthermore, at each epoch time, items of different classes may be sold or moved to a lower quality class or stay in the same class. These items are priced according to their quality, and costs are incurred as items lose quality. Based on observing the history of the inventory level and prices, we propose recursive estimators as well as predictors for the joint distribution of the accumulated losses and the state of the environment.

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