Decentralized Model for a Two-Stage Supply Chain with Exogenous Demand

This paper presents a formal mathematical model for managing problems of stochastic demands; confronting many industries in the society today. We consider a two- stage supply chain where the upstream manufacturer (stage2) must always fill exogenous demands from the downstream manufacturer (stage1) using  two types of expediting : Overtime production and outsourcing.Key words: Supply chain management(SCM), Supply chain(SC), Inventory, backorder, Opti-mality

Managing production-inventory systems with scarce resources

We consider the problem of managing production in a production-inventory system where a firm is subject to an allowance (a limit) on either the amount of input it can use or the amount of output it can produce over a specified compliance period (in addition to being subject to a constraint on the production capacity). Examples of such settings are numerous and include those where limits are placed on the use of scarce natural resources as input or on the amount of waste or harmful pollution generated by production as output. We study the structure of the optimal production policy for such systems and show that it is determined by dynamic thresholds that depend only on the sum of the on-hand inventory level and the remaining allowance. We provide an effective approximate solution approach that can compute these thresholds efficiently while retaining their essential properties. We examine the differences between how an allowance constraint and a constraint on production capacity affect production decisions and show that they exhibit opposite effects over time. We also examine, in the context of an extended version of the problem where both the allowance amount and the production capacity are endogenous, optimal investments in allowance and production capacity and the impact of both on firm profit. We also consider the optimal demand fulfillment policy in settings where the firm can decide whether to back-order or to reject demand that cannot be satisfied from on-hand inventory. The online appendix is available at https://doi.org/10.1287/msom.2016.0603 . </jats:p

An Investigation of Buyers’ Forecast Sharing and Ordering Behavior in a Two-Stage Supply Chain

Profitably balancing demand and supply is a continuous challenge for companies under changing market conditions, and the potential benefit of collaboration between supply chain partners cannot be overlooked by any firm who strives to succeed. One of the key elements to successful collaboration is sharing of forecast information between supply chain partners. However, when supply shortage is expected, buyers may inflate order quantities and/or order forecasts to secure sufficient supply. An important question that arises is how the supplier should allocate inventory to customers when shortage exists. Literature shows that certain allocation policies can reduce buyers’ order inflation behavior. However, this has not yet been empirically shown for order forecast inflation behavior, nor incorporating the behavioral aspects of decision makers. In this dissertation, through behavioral experiments using a supply chain simulation game, we investigate the impact of different capacity allocation mechanisms and information disclosures of a supplier on buyers’ forecast sharing and ordering behavior. We first investigate the buyers’ order forecast sharing behavior in a single-suppliertwo- buyer supply chain. Our behavioral study shows that forecast-accuracy based allocation, where the supplier allocates more capacity to the buyer with better forecast accuracy, can significantly improve order forecast accuracy relative to uniform allocation, where the supplier equally allocates capacity to the buyers. Under both policies, particularly uniform allocation, the order forecast accuracy is improved with the supplier’s information disclosure on the policy. Next, we focus on buyers’ ordering behavior, and formulate a single-supplier-single-buyer base-stock inventory model under constrained supply. We validate our analytical results through numerical simulation, which is then extended to the single-supplier-two-buyer case. We next compare the buyers’ optimal decisions from the simulation with the actual decisions in our behavioral study, and find that buyers in the experiment show a significantly lower profit performance ranging from 0.8% to 14.1%. Using structural estimation modeling techniques, we estimate the buyers’ perceived overage/underage cost ratios from the experiment, and conclude by conducting a detailed analysis on the factors that affect buyers’ ordering decisions. In addition to academic contributions, our results provide insights for practitioners to understand buyers’ strategic behavior and help with designing capacity allocation strategies

Managing Material and Financial Flows in Supply Chains

<p>This dissertation studies the integration of material and financial flows in supply chains, with the goal of examining the impact of cash flows on the individual firm's decision making and the overall supply chain efficiency. We develop analytical models to provide effective policy recommendations and derive managerial insights.</p><p>We first consider a credit-constrained firm that orders inventory to satisfy stochastic demand in a finite horizon. The firm provides trade credit to the customer and receives it from the supplier. A default penalty is incurred on the unfulfilled payment to the supplier. We utilize an accounting concept of working capital to obtain optimal and near-optimal inventory policies. The model enables us to suggest an acceptable purchasing price offered in the supplier's trade credit contract, and to demonstrate how liquidity provision can mitigate the bullwhip effect. We then study a joint inventory and cash management problem for a multi-divisional supply chain. We consider different levels of cash concentration: cash pooling and transfer pricing. We develop the optimal joint inventory replenishment and cash retention policy for the cash pooling model, and construct cost lower bounds for the transfer pricing model. The comparison between these two models shows the value of cash pooling, although a big portion of this benefit may be recovered through optimal transfer pricing schemes. Finally, we build a supply chain model to investigate the material flow variability without cash constraint. Our analytical results provide conditions under which the material bullwhip effect exists. These results can be extended to explain the similar effect when financial flows are involved. In sum, this dissertation demonstrates the importance of working capital and financial integration in supply chain management.</p>Dissertatio

Strategic inventory placement in multi-echelon supply chains : three essays

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2008.Includes bibliographical references (p. 134-137).A central question in supply chain management is how to coordinate activities and inventories over a large number of stages and locations, while providing a high level of service to end customers. One theoretically and practically important methodology for addressing this problem is the guaranteed service (GS) framework, in which the stages of the supply chain operate according to base stock policies, and prove guaranteed service to one another. Demand is assumed to be bounded. Previous work on GS models has established very effective algorithms for finding optimal safety stock placement. In the first essay of the thesis, we show how these methods can be generalized to handle problems with capacity constraints. Furthermore, we investigate orders that are censored (reduced so as to prevent deliveries greater than what can be processed). We find safety stock reductions, sometimes even below what was needed in the no-constraint situation. In the second essay, we investigate a situation in which different parts of the supply chain are controlled by different parties, each of which selfishly applies its own GS optimization. We find that provided that the parties can agree on the right service time between them, it will be in their own interests to maintain the globally optimal solution (i.e., the system is incentive compatible). This suggests that the GS framework is better suited for coordination, than are other frameworks analyzed in the coordination literature. Finally, in the third essay, we apply the GS framework to a setting where orders are driven by forecasts and schedules, rather than by past demand as in previous GS work. We show precisely how the demand bound can be replaced by a bound on forecast errors, and that existing optimization methods can be used.(cont.) In a case study, we obtained data from the supply chain of an electronic test system, as well as characterized the forecasting process. We found that incorporating the forecast process led to 25% reduction of safety stocks.by Tor Schoenmeyr.Ph.D

Gestion des stocks et de la production intégrant des retours de produits

De nombreux retours de produits dus au recyclage et à la réutilisation des déchets se développent dans le but de préserver les ressources naturelles limitées de notre planète. Ces nouveaux flux interagissant avec les flux de production traditionnels, il est important de les piloter de façon à satisfaire au mieux les demandes des clients et minimiser l'encours dans la chaîne logistique. Nos travaux s'inscrivent dans cette démarche. Nous nous plaçons dans un contexte où la capacité de production est limitée et nous considérons un problème opérationnel de gestion des stocks et de la production intégrant des flux de retours. Nous modélisons trois problèmes de production et de stockage à temps continu, avec des capacités de production limitées, des délais aléatoires et des coûts linéaires. Le premier prenant en compte la probabilité qu'un produit puisse être réutilisé comme produit fini ou seulement comme produit semi-fini (par partie), le deuxième présentant un problème où la réutilisation d'un retour comme produit fini nécessite une étape de remise à neuf et le troisième modélisant un système où les clients préviennent à l'avance du renvoi potentiel de leurs produits. Outre la caractérisation des politiques optimales de gestion, une part importante de nos contributions réside dans l'évaluation des performances de différentes politiques heuristiques et l'étude de l'impact de la capacité de production sur celles-ci. Enfin, nous nous servons dans tout ce document d'outils permettant la caractérisation des politiques optimales. La dernière partie de ce document vise à développer ces outils et à permettre l'étude de l'effet des paramètres d'un système formulé en processus de décision Markovien sur la politique optimale de celui-ci.Flows of returns due to recycling and reusing waste are developing in order to preserve the limited natural resources of our planet. These new flows interact with the traditional production flows. Therefore, in order to provide customers with the best service level and minimize the stock in the supply chain, the control of the return flows appears to be of highest importance. We address this problem by modeling a situation with a limited porduction capacity and we consider an operational production/inventory problem that incorporates flows of returns. We model three continuous-time production/inventory problems with limited produc- tion capacities, random lead times, and linear costs. In the first problem we take into account the probability that a product can be reused as a finished product or only as semi-finished product (by parts), in the second problem we include a step of remanufac- turing before reusing the returned product, and in the third problem we consider a system with product returns that are announced in advance by the customers. Apart from the caracterization of the optimal policies for these cases, the performance assessments of some heuristic policies and the study of the poduction capacity effect on these heuristic policies stand as main contributions. Throughout this work we have used existing tools to characterize optimal policies for different Markov decision processes. The last chapter aims to improve these tools and enable us to study the influence of several system parameters on its optimal policy.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF