Mohamed Zied Babai

Kedge Business School · Operations Management and Information Systems

Inventory systems are largely analyzed in the literature under the common assumption of backorders due to the complexity of lost sales. In this paper, we consider a two-echelon inventory system composed of a central warehouse and multiple local warehouses subject to lost sales. The demand faced by each local warehouse is a Poisson process and the s...

The rapid spread of the COVID-19 virus and the massive influx of patients exceeded the intensive care units capacity limit. Hospitals have engaged community partners to request resources or transfer patients to facilities with available resources. This setting fosters the need for rationing decisions to allocate scarce resources consistently, rathe...

This paper presents a solution of a generalized newsvendor problem with supply disruption and dual sourcing, where the underlying product price and demand are correlated and evolve randomly over time. We contribute to the literature by employing a non-stationary model for demand, and proposing a novel solution methodology using the change of measur...

Over the last decade, additive manufacturing (AM) has received an increased attention as many manufacturing companies have increasingly adopted new technologies to capture new opportunities. This research identifies the impacts of AM on the supply chain when compared to the case of conventional manufacturing. Through an empirical investigation cond...

The inventory management of medical items in humanitarian operations is a challenging task due to the intermittent nature of their demand and long replenishment lead-times. While effective response to emergency results in inventory build-up which saves human lives, excess inventories could be intentionally burnt or donated which is costly for human...

Customer expectations on fulfillment responsiveness is growing with prevalent home delivery practices via e-retails or omnichannel operations. Tight responsiveness requirements, such as x-hour delivery, requires physical availability of inventory near demand locations. This raise a need for a broad and dense inventory network and a smart inventory...

Temporal aggregation is an intuitively appealing approach to deal with demand uncertainty. There are two types of temporal aggregation: non-overlapping and overlapping. Most of the supply chain forecasting literature has focused so far on the former and there is no research that analyses the latter for auto-correlated demands. In addition, most of...

Forecasting of the cumulative distribution function (CDF) of demand over lead time is a standard requirement for effective inventory replenishment. In practice, while the demand for some items conforms to standard probability distributions, the demand for others does not, thus making it challenging to estimate the CDF of lead-time demand. Distribut...

Demand forecasts are the basis of most decisions in supply chain management. The granularity of these decisions lead to different forecast requirements. For example, inventory replenishment decisions require forecasts at the individual SKU level over lead time, whereas forecasts at higher levels, over longer horizons, are required for supply chain...

One of the critical issues that an airline faces in its day-to-day operations is a correct prognosis of the necessary quantity of spare parts that are continuously fed into unexpected maintenance operations. Indeed, there is a critical need for accurate forecasting methods to predict the demand of these spare parts in order to minimize the so-calle...

Over the last decade, Additive Manufacturing has received an increased attention as many manufacturing companies have increasingly adopted new technologies to capture new opportunities. This research identifies the impacts of Additive Manufacturing (AM) on the supply chain when compared to the case of conventional manufacturing. Through an empirica...

Effective inventory management has a direct influence on monetary savings, high customer service level and product quality and thus plays an essential role in a company’s economic and strategic performance. Forecasting and inventory models for aviation logistics are essential in commercial aviation. The objective of this paper is to study the probl...

Spare parts are often associated with intermittent demand patterns that render their forecasting a challenging task. Forecasting of spare parts demand has been researched through both parametric and non-parametric approaches. However, little has been contributed in this area from a Bayesian perspective, and most of such research is built around the...

A base-stock inventory system for perishables with Markovian demand and general lead-time and lifetime distributions is investigated. Using a queueing network model, we derive explicit expressions of the stationary distribution of the inventory state together with the total expected cost in a base-stock system with lost-sales. Next, we show some mo...

Nowadays, due to the increasing complexity of business environment, especially demand uncertainty, supply chain managers need to establish more-effective sourcing and distribution strategies to ensure high customer service and low stock costs. To overcome this challenge multi-echelon network structures and alternative distribution strategies such a...

Online car hailing platforms are rapidly gaining popularity. Unlike most two-sided markets, these platforms have pricing power. The price for a specific customer ride request affects the number of interested drivers and the likelihood that a customer will accept a selected driver (and not opt for a regular taxi service). This study determines the o...

A plethora of methods have been developed in the last decades to deal with the inventory forecasting of intermittent demand items. These methods belong to the parametric and non-parametric approaches, the artificial neural networks approach and the fuzzy logic-based techniques among others. Most of the parametric methods represent variations of the...

Perishable items with a limited lifespan and intermittent/erratic consumption are found in a variety of industrial settings: dealing with such items is challenging for inventory managers. In this study, a periodic inventory control system is analysed, in which items are characterised by intermittent demand and known expiration dates. We propose a n...

Various approaches have been considered in the literature to improve demand forecasting in supply chains. Among these approaches, non-overlapping temporal aggregation has been shown to be an effective approach that can improve forecast accuracy. However, the benefit of this approach has been shown only under single exponential smoothing (when it is...

We consider inventory systems for perishables with two-supply modes (a regular mode and an emergency one) characterized by different lead-times and costs. We investigate the value of dual-sourcing in the context of perishable items with a fixed or exponential lifetime. The inventory is controlled according to a base-stock policy where the emergency...

Many bootstrapping approaches have been proposed in the academic literature for non-parametric demand forecasting. Two approaches have been developed to deal particularly with intermittent demands. A first approach that samples demand data by using a Markov chain to switch between no demand and demand periods and a second approach that separately s...

Accurate demand forecasts are essential to the inventory control of spare parts. There is a plethora of statistical methods developed in the academic literature to deal with the forecasting of spare parts demand. These methods belong to the parametric and the non-parametric approaches. Within the second approach, the bootstrapping methods are the m...

The continuous review base-stock policy under the lost sales assumption has been extensively studied in the inventory literature. However, most of the research that deals with the optimal policy parameter determination under compound Poisson demand focuses on the stuttering Poisson case. In this paper, we extend earlier research by providing a meth...

Redundancy is often essential for achieving high system availability. An additional benefit of installing redundant components is that the total system load can be shared among components, thus preventing fast deterioration. On the one hand, this provides an incentive to replace failed components as soon as possible, as a component failure increase...

The operations management literature is abundant in discussions on the benefits of information sharing in supply chains. However, there are many supply chains where information may not be shared due to constraints such as compatibility of information systems, information quality, trust and confidentiality. Furthermore, a steady stream of papers has...

The fill rate is the most widely applied service level measure in industry and yet there is minimal advice available on how it should be differentiated on an individual Stock Keeping Unit (SKU) basis given that there is an overall system target service level. The typical approach utilized in practice, and suggested in academic textbooks, is to set...

Nowadays, Companies have to deal with uncertain demand which is more difficult to handle when it has a non-stationary pattern. Simultaneous decrease of customer service and increase of stock costs are the most significant effects of such demand uncertainty. To deal with this issue, inventory optimization models must be adapted to cover a multi-eche...

Temporal demand aggregation has been shown in the academic literature to be an intuitively appealing and effective approach to deal with demand uncertainty for fast moving and intermittent moving items. There are two different types of temporal aggregation: non-overlapping and overlapping. In the former case, the time series are divided into consec...

Practical experience and scientific research show that there is scope for improving the performance of inventory control systems by delaying a replenishment order that is otherwise triggered by generalised and all too often inappropriate assumptions. This paper presents the first analysis of the most commonly used continuous (s, S) policies with de...

Intermittent demand items dominate service and repair inventories in many industries and they are known to be the source of dramatic inefficiencies in the defence sector. However, research in forecasting such items has been limited. Previous work in this area has been developed upon the assumption of a Bernoulli or a Poisson demand arrival process....

Despite the evidence of benefits of information sharing, there are many supply chains that are unable to share information due to constraints such as compatibility of information systems, information quality, trust and confidentiality. Furthermore, a steady stream of papers has explored a phenomenon known as Downstream Demand Inference (DDI) where...

Information sharing has been identified, in the academic literature, as one of the most important levers to mitigate the bullwhip effect in supply chains. A highly-cited article on the bullwhip effect has claimed that the percentage inventory reduction resulting from information sharing in a two level supply chain, when the downstream demand is aut...

Although intermittent demand items dominate service and repair parts inventories in many industries, research in forecasting such items has been limited. A critical research question is whether one should make point forecasts of the mean and variance of intermittent demand with a simple parametric method such as simple exponential smoothing or else...

ABC classifications can be constructed based on a wide range of approaches (varying from formal multi-criteria optimization models to more subjective approaches like the analytic hierarchy processes). Several multi-criteria inventory classification (MCIC) models in particular have recently been proposed in the academic literature. However, even in...

A number of multi-criteria inventory classification (MCIC) methods have been proposed in the academic literature. However, most of this literature focuses on the development and the comparison of ranking methods of stock keeping units (SKUs) in an inventory system without any interest in the original and most important goal of this exercise which i...

Intermittent demand items account collectively for considerable proportions of the total stock value of any organization. Forecasting the relevant inventory requirements constitutes a very difficult task and most work in this area is based on Croston's estimator that relies upon exponentially smoothed demand sizes and inter-demand intervals. This m...

Nowadays companies must look to develop new distribution strategies in order to achieve the required performance from their supply chain. In this quest, companies wonder about the consistency of their distribution strategies with the types of products they are selling. This article deals with the issue of product segmentation and distribution strat...

Earlier research on the effects of nonoverlapping temporal aggregation on demand forecasting showed the benefits associated with such an approach under a stationary AR(1) or MA(1) processes for decision making conducted at the disaggregate level. The first objective of this note is to extend those important results by considering a more general und...

Spare parts are known to be associated with intermittent demand patterns and such patterns cause considerable problems with regards to forecasting and stock control due to their compound nature that renders the normality assumption invalid. Compound distributions have been used to model intermittent demand patterns; there is however a lack of theor...

In this paper, we propose a new method for determining the optimal base-stock level in a single echelon inventory system where the demand is a compound Erlang process and the lead-time is constant. The demand inter-arrival follows an Erlang distribution and the demand size follows a Gamma distribution. The stock is controlled according to a continu...

Aris Syntetos, David Lengu and Mohamed Zied Babai rectify a paper authored by them on the demand distributions of spare parts. When reflecting on the paper's methodology, an error was identified by them. The goodness-of-fit of the various distributions considered in that study was assessed by employing the Kolmogorov-Smirmov (K-S) test. When calcul...

In this paper the relative effectiveness of top-down (TD) versus bottom-up (BU) strategies is compared for forecasting the aggregate demand. We assume that the subaggregate demand follows an Autoregressive Moving Average process of order one and a Single Exponential Smoothing (SES) procedure is used to forecast demand. This demand process is often...

Demand forecasting performance is subject to the uncertainty underlying the time series an organization is dealing with. There are many approaches that may be used to reduce uncertainty and thus to improve forecasting performance. One intuitively appealing such approach is to aggregate demand in lower-frequency “time buckets.” The approach under co...

Demand forecasting performance will be challenged by demand dispersion underlying the time series related to the Stock Keeping Units (SKUs). Among the strategies that may be used to reduce the demand dispersion, an intuitively appealing approach is to aggregate demand in lower-frequency 'time buckets'. This paper focuses on the impact of non-overla...

The ARIMA(0,1,1) demand model has been analysed extensively by researchers and used widely by forecasting practitioners due to its attractive theoretical properties and empirical evidence in its support. However, no empirical investigations have been conducted in the academic literature to analyse demand forecasting and inventory performance under...

In this paper, we consider the multicriteria inventory classification problem. We propose a new classification algorithm referred to as Constructive Order Classification Algorithm (COCA). This algorithm is based on some simple priority rules and aims to standardize the classification and provide relative stability in the classification through a co...

The service sector is the largest sector of the economy in most industrialized nations, and is fast becoming the largest sector in developing nations as well. Driven by today's new business environment, including advanced telecommunications, accelerated business globalization, increased automation and highly on-demand and competitive innovations, t...

In this paper we extend earlier work that analyzes a single echelon single item base-stock inventory system where Demand is modeled as a compound Poisson process and the lead-time is stochastic. The extension consists in considering a cost oriented system where unfilled demands are lost. The case of partial lost sales is assumed. We first model the...

Intermittent demand is characterized by occasional demand arrivals interspersed by time intervals during which no demand occurs. These demand patterns pose considerable difficulties in terms of forecasting and stock control due to their compound nature, which implies variability both in terms of demand arrivals and demand sizes. An intuitively appe...

A number of Multi Criteria Inventory Classification (MCIC) methods have been proposed in the academic literature. However, most of this literature focuses on the development of ranking methods of stock keeping units (SKUs) in an inventory system without any interest in the original and mostimportant goal of this exercise which is the inventory pe...

Demand forecasting performance is subject to the variability and uncertainty underlying the time series related to the Stock Keeping Units (SKUs) an organisation is dealing with. Different strategies may be used to reduce the demand variability and forecast error, thus improve the forecasting performance. One such strategy is to aggregate demand in...

Demand forecasting performance is subject to the variability and uncertainty underlying the time series related to the Stock Keeping Units (SKUs) an organisation is dealing with. Different strategies may be used to reduce the demand variability and forecast error, thus improve the forecasting performance. One such strategy is to aggregate demand in...

Spare parts have become ubiquitous in modern societies, and managing their requirements is an important and challenging task with tremendous cost implications for the organisations that are holding relevant inventories. Demand for spare parts arises whenever a component fails or requires replacement, and as such the relevant patterns are different...

Demand forecasting performance is subject to the variability underlying the time series related to the Stock Keeping Units (SKUs) an organisation is dealing with. There are many strategies that may be used to reduce the demand variability and thus to improve the forecasting performance. An intuitively appealing such a strategy is to aggregate deman...

Contrary to expectations, the use of electronic marketplaces still remains marginal and the credibility of such technology is constantly undermined in practice. However, some major business groups have acted as forerunners and have invested in electronic marketplaces because they are aware of the substantial benefits that could stem from their impl...

The standard method to forecast intermittent demand is that by Croston. This method is available in ERP-type solutions such as SAP and specialised forecasting software packages (e.g. Forecast Pro), and often applied in practice. It uses exponential smoothing to separately update the estimated demand size and demand interval whenever a positive dema...

We analyse a single echelon single item inventory system where the demand and the lead time are stochastic. Demand is modelled as a compound Poisson process and the stock is controlled according to a continuous time order-up-to (OUT) level policy. We propose a method for determining the optimal OUT level for cost oriented inventory systems where un...

This chapter’s primary focus is limited to the bootstrap statistical method of forecasting and its application to spare parts inventory. Following a rough chronological order, first, the chapter describes Efron’s bootstrap method for estimating a sampling distribution based on an observed sample, as well as some of his extensions of his initial wor...

Parametric approaches to stock control rely upon a demand distributional assumption and the employment of an appropriate forecasting procedure for estimating the moments of such a distribution. For the case of fast demand items the Normality assumption is typically sufficient. However, spare parts typically exhibit intermittent or irregular demand...

This article empirically investigates the extension of the use of an aggregation-disaggregation forecasting approach for intermittent demand (ADIDA) to fast-moving demand data, addressing the need of supply chain managers for accurate forecasts. After a brief introduction to the framework and its background, an experiment is set up to examine its p...

Managing spare parts inventories is a challenging task and can benefit considerably from any information on the failure rate of the parts. It has often been considered in the stock control literature that parts' failures are only random, caused by external events which results in the assumption of constant failure rate and therefore the considerati...

Wholesalers add value to the products they deal with by essentially bringing them closer to the end consumers. In that respect, the effective control of stock levels becomes an important measure of operational performance especially in the context of achieving high customer service levels. In this paper, we address issues pertinent to forecasting a...

We propose a new method for determining order-up-to levels for intermittent demand items in a periodic review system. Contrary to existing methods, we exploit the intermittent character of demand by modelling lead time demand as a compound binomial process. In an extensive numerical study using Royal Air Force (RAF) data, we show that the proposed...

ABC inventory classifications are widely used in practice, with demand value and demand volume as the most common ranking criteria. The standard approach in ABC applications is to set the same service level for all stock keeping units (SKUs) in a class. In this paper, we show (for three large real life datasets) that the application of both demand...

The periodic (T,s,S) policies have received considerable attention from the academic literature. Determination of the optimal parameters is computationally prohibitive, and a number of heuristic procedures have been put forward. However, these heuristics have never been compared in an extensive empirical study. Such an investigation on 3055 SKUs is...

Spare parts are typically associated with an intermittent demand structure meaning that demand arrives infrequently. Moreover, demand, when it occurs, may also be variable, perhaps highly so. Parametric approaches to inventory control rely upon a hypothesised demand distribution. A number of authors have suggested that compound Poisson distribution...

We propose a new method for approximating the optimal order-up-to level in inventory systems with compound Poisson demand process and stochastic lead-time. The approximations are derived for cost oriented inventory systems where unfilled demands are backordered. The condition under which the system behaves like a Make-To-Order system is also discus...

We propose a new method for approximating the optimal order-up-to level in inventory systems with compound Poisson demand process and stochastic lead-time. The approximations are derived for cost oriented inventory systems where unfilled demands are backordered. The condition under which the system behaves like a Make-To-Order system is also discus...

In this paper we propose a modification to the standard forecasting, periodic order-up-to-level inventory control approach to dealing with intermittent demand items, when the lead-time length is shorter than the average inter-demand interval. In particular, we develop an approach that relies upon the employment of separate estimates of the inter-de...

A new forecast-based dynamic inventory control approach is discussed in this paper. In this approach, forecasts and forecast uncertainties are assumed to be exogenous data known in advance at each period over a fixed horizon. The control parameters are derived by using a sequential procedure. The merits of this approach as compared to the classical...

Purpose Spare parts have become ubiquitous in modern societies and managing their requirements is an important and challenging task with tremendous cost implications for the organisations that are holding relevant inventories. An important operational issue involved in the management of spare parts is that of categorising the relevant stock keeping...

In this paper, two approaches of production-inventory control are considered: the future requirements-based approach and the inventory consumption-based approach. We focus on a single-stage and single-item inventory system under non-stationary demand, information about which is provided by means of forecasts. Forecasts and forecast uncertainties ar...

Purpose The technology of time temperature integrators (TTI) is used to ensure the safety and quality of temperature sensitive goods such as food and drugs along their entire lifespan. This work aims to provide a better understanding of potential benefits that can be expected from the use of TTIs in terms of supply chain improvement. Design/method...

In this paper, we analyze a single-stage and single-item inventory control system with non-stationary demand and uncertain system parameters. We propose two extensions of a previous work on the dynamic reorder point policy (the (r_k, Q) policy). In the first extension, we include three types of uncertainties pertaining to the demand uncer...

In this paper, we analyze forecast based inventory control policies for a non-stationary demand. We assume that forecasts and the associated uncertainties are given at the beginning of the horizon of forecasts. Two forecast based reorder point policies are proposed : the (rk;Q) and the (rk;Qk) policies. These dynamic policies represent an extension...

The efficient management of supply chain flows is an important concern that is considered by enterprises as a lever enabling to improve the customer service level at low costs. Several investigations deal with this issue by developing tools for a better flow management. Within this framework, our thesis proposes new flow management policies. In the...

Le pilotage de flux dans les chaînes logistiques représente un enjeu majeur pour les entreprises qui leur permet d’améliorer la qualité du service vis-à-vis des clients tout en réduisant les coûts. Plusieurs travaux s’intéressent à cette problématique en proposant des outils pour un meilleur pilotage. Cette thèse s’inscrit dans le cadre de ces trav...

In this paper, we provide a literature review on inventory management policies. Two approaches are distinguished : the standard inventory management approach and the advance demand information based approach. We focus on the advance demand information based approach. In particular, we study a pure single-stage and single-item inventory system where...

A new forecast-based dynamic inventory control approach is discussed in this paper. In this approach, forecasts and forecast uncertainties are assumed to be exogenous data known in advance at each period over a fixed horizon. The control parameters are derived by using a sequential optimization procedure. The merits of this approach as compared to...

Wholesalers add value to the products they deal with, by essentially bringing them closer to the end consumers. In that respect, the effective control of stock levels becomes an important measure of operational performance especially in the context of achieving high customer service levels. In this paper, we address issues pertinent to forecasting...

Wholesalers add value to the products they deal with, by essentially bringing them closer to the end consumers. In that respect, the effective control of stock levels becomes an important measure of operational performance especially in the context of achieving high customer service levels. In this paper, we address issues pertinent to forecasting...