Yacine Rekik

A comprehensive analysis of the Newsvendor model with unreliable supply

A single-period, uncertain demand inventory model is analyzed under the assumption that the quantity ordered (produced) is a random variable. We first conduct a comprehensive analysis of the well known single period production/inventory model with random yield. Then, we extend some of the results existing in literature: our main contribution is to show that earlier results are only valid for a certain range of system parameters. Under the hypothesis that demand and the error in the quantity received from supplier are uniformly distributed, closed-form analytical solutions are obtained for all values of parameters. An analysis under normally distributed demand and error is also provided. The paper ends with an analysis of the benefit achieved by eliminating errors.

Improving the performance of retail stores subject to execution errors: coordination versus RFID technology

This paper analyzes a Newsvendor type inventory model in which a manufacturer sells a single product to a retailer store whose inventory is subject to errors stemming from execution problems. Hence, within the store, all of the products are not available on shelf for sales either because the replenishment of the shelf from the backroom is subject to execution errors that mainly result in products lost in the backroom or products misplaced on the other shelves of the store. We compare two situations: in the first situation, the two supply chain actors are aware of errors and optimize their ordering decisions by taking into account this issue. The second situation deals with the case where an advanced automatic identification system such as the Radio Frequency Identification technology is deployed in order to eliminate errors. Each situation is developed for three scenarios: in the centralized scenario, we consider a single decision-maker who is concerned with maximizing the entire supply chain’s profit; in the decentralized uncoordinated scenario, the retailer and the manufacturer act as different parties and do not cooperate. The third scenario is the decentralized coordinated scenario where we give conditions for coordinating the channel by designing a buyback contract.

Exploring inventory systems sensitive to shrinkage – analysis of a periodic review inventory under a service level constraint

Motivated by empirical evidence, this article focuses on the behaviour of a store inventory exposed to inventory record inaccuracy. The inventory, controlled by an infinite horizon, single-stage, single-product periodic-review policy, is subject to shrinkage errors that cause a difference between the physical and information system inventory levels. We model a set of scenarios depending on the technology available to track shrinkage in the store. In scenarios where a technology such as Radio Frequency IDentification (RFID) is not used, inventory is controlled by estimating the expected shrinkage rate. We assume that an inspection process is performed at a regular frequency of N selling periods. We analyse two situations that permit management of the joint ordering and inspection policy based on the information the inventory manager has on shrinkage errors. A comparison between these two situations permits us to analyse the impact of shrinkage errors and the value of taking into account the inventory inaccuracy issue when optimising the inventory and inspection policies. The deployment of the RFID technology produces two benefits: total visibility of the shrinkage rate and the elimination of shrinkage errors. A comparison of the scenarios enables us to evaluate the economic impact of inventory record inaccuracies, which can be significant, particularly in systems with a poor estimation of the error parameter as well as with a high inspection cost.

Inventory routing problems in a context of vendor-managed inventory system with consignment stock and transshipment

The inventory routing problem involves the integration and the coordination of two components of the logistics value chain: the inventory management and the vehicle routing decisions. In fact, the aim is to jointly decide on the distribution tour, from a distribution centre to a set of locations, and on the inventory policy for each location. Although many research investigations show great interest in policies such as transshipment or dynamic routings on the distribution system performances, these approaches are often criticised in practice as being too restrictive. In this article, we consider the inventory routing framework in a supplier integration context, i.e. a vendor-managed inventory with a consignment stock policy. Under such framework, we show that the transshipment brings more benefits than the classical context. In particular, we consider the case of static routings and we numerically show that transshipment permits to better optimise the distribution tours and to improve the global performance of the supply network.

Inventory management subject to multiplicative inaccuracies

The standard literature on inventory modelling is rarely differentiating between the inventory records and the physical inventory. In the recent years, some empirical studies highlighted that errors and inventory perturbations may occur in the inventory system. Such errors result in a gap between what the informational system (IS) shows and what is actually available for sales and used to satisfy the demand. The impact of such errors is particularly important in a wholesaling/e-retailing context where customer’ demands are remotely satisfied based on the inventory records shown in the IS. These errors could be modelled by an additive or multiplicative structure depending on the link between the error variability and the ordered quantity. The aim of the paper is to extend the existing literature by developing an inventory framework that permits the analysis and the performance improvement of an inventory system subject to a multiplicative errors setting. The multiplicative and stochastic settings also known as the stochastically proportional modelling of errors is not well developed in the literature despite the fact that such an assumption bears considerable association with reality. We provide comprehensive analytical and numerical studies and we also complete our contribution by a comparison between the additive and the multiplicative error settings where we derive interesting managerial insights about the impact of wrongly modelling errors. We also focus on the benefit of applying our results compared with the case where errors are ignored or not known.

Execution errors in retail supply chains: analysis of the case of misplaced products

This article considers the situation of a supply chain consisting of a manufacturer and a retail store which faces an uncertainty not only in consumer demand but also in inventory records. Among execution errors that induce an uncertainty in inventory records are undetected supplier unreliabilities, unrecorded item movements (either during the receiving process or within the store), theft, damaged products, etc. In our work, we assume that such inventory inaccuracies are introduced by misplacement-type errors that occur within the store, i.e. the whole quantity of products that is received from the manufacturer is not available on shelf to satisfy consumers’ demand either because within the store, the replenishment process from the backroom to shelves is prone to errors (e.g. products are lost during this transfer, some of the products are forbidden in the backroom, other products are put on the wrong shelves, etc…) or products are moved and put on other shelves by consumers during their visit to the store. The framework we consider to model the misplaced products issue is a decentralised Newsvendor model. Within this setting, we analyse four scenarii. Each scenario can be characterised by (i) whether the manufacturer and the retailer are aware of misplacement errors that occur in the store or not (they are not aware of misplacement errors or even that they know the existence of errors, they choose to ignore them) (ii) whether there is a coordination between actors or not. Based on these scenarii, our aim is to evaluate the benefit of having information on errors and optimising the system by taking this information into account as well as the benefit of coordinating the channel.

Enriching demand forecasts with managerial information to improve inventory replenishment decisions: exploiting judgment and fostering learning

This paper is concerned with analysing and modelling the effects of judgmental adjustments to replenishment order quantities. Judgmentally adjusting replenishment quantities suggested by specialized (statistical) software packages is the norm in industry. Yet, to date, no studies have attempted to either analytically model this situation or practically characterize its implications in terms of ‘learning’. We consider a newsvendor setting where information available to managers is reflected in the form of a signal that may or may not be correct, and which may or may not be trusted. We show the analytical equivalence of adjusting an order quantity and deriving an entirely new one in light of a necessary update of the estimated demand distribution. Further, we assess the system’s behaviour through a simulation experiment on theoretically generated data and we study how to foster learning to efficiently utilize managerial information. Judgmental adjustments are found to be beneficial even when the probability of a correct signal is not known. More generally, some interesting insights emerge into the practice of judgmentally adjusting order quantities.

A bi-objective inventory routing problem by considering customer satisfaction level in context of perishable product

In this paper, we study a joint inventory and routing problem (IRP) for the food supply chain and we investigate the impact of customer satisfaction level under the optimization of the total expected cost. We propose a new bi-objective mathematical model by taking into account multi capacitated vehicles for perishable products from one supplier to many customers by considering total traveling time. The first objective in our optimization minimizes the different inventory and distribution costs (holding cost, shortage cost, ordering cost, fixed, variable transportation cost and recycling cost) while the second objective considers the customer satisfaction level, which is measured based on delays of vehicles. We consider perishable items and we also manage in this framework their shelf life (expiration date). The proposed framework is modelled as a mixed-integer linear program and is solved by using the software GAMS.

A Periodic Review Inventory Model subject to Shrinkage Type Errors: Impact of RFID

Various execution errors and factors can create a difference between the expected and the effective physical and information flows within an inventory system. We consider a finite horizon, single-stage, single-product periodic-review inventory in which inventory records are inaccurate. We assume that inventory inaccuracies are introduced by shrinkage type errors that occur within the store. We propose three ways permitting to manage the inventory system based on the information we have on shrinkage errors. The comparison between the three approaches permits us to analyse the impact of shrinkage errors and the value of the Radio Frequency Identification (RFID) technology on the inventory system.

Inventory Routing Problem for Perishable Products by Considering Customer Satisfaction and Green Criteria

This paper presents a new model for Inventory Routing Problem (IRP) considering simultaneously economic criteria, customer satisfaction level and environmental aspect for perishable products with expiration date. For this consideration, a multi-objective mathematical model has been developed. The first objective focuses on traditional inventory and distribution costs as well as recycling cost of perished products. The second objective concerns in customer satisfaction by minimization of three criteria, such as the number of delays (deliver after time windows), the quantity of backordered, and the frequency of backorders. The third objective considers Greenhouse Gas (GHG) emission, produced by different IRP activities. The proposed model is also enabled to investigate the possibility of using diesel and electrical vehicles in urban transportation. In order to cope with complexity of proposed model, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is tuned and applied. Finally, sensitivity analysis is performed to investigate the effects of variation of customer satisfaction and green aspects in economic side.