Supply chain agility has been receiving a lot of attention in recent literature as a way for organizations to become more responsive to change and improve customer service levels. However, agility is typically dealt with qualitatively, and organizations are usually unsure of the steps to take to improve their agility and the customer service level to target. This research studies supply chain agility based on a case study of Intel Corporation, a large semiconductor manufacturer. Here, agility is defined as the ability to satisfy customer demands by reacting effectively to changes in market stimuli. Reacting effectively does not mean reacting to every change in supply or demand. Doing so means increasing supply chain variability unnecessarily, which is amplified by the bullwhip effect. The essence of supply chain agility is determining the degree to which variability should be managed through artificial means such as safety stock, and appropriate triggers for changing production levels and inventory targets. The purpose of this research is to examine factors that influence supply chain agility and identify a cost-effective plan for achieving it. The first phase addresses the problem of identifying target inventory and customer service levels based on regression analysis of historical data and financial analysis of inventory holding costs and stock-out costs. The impact of three factors (forecast error, order lead-time, and demand variability) on the relationship between inventory and customer service level is also examined. The second phase of the research evaluates strategies for production and inventory control with the goal of finding the appropriate trade-off between minimizing cost (of holding inventory and stock-outs) and minimizing variability. Control policies based on the Exponentially Weighted Moving Average (EWMA) control chart with control limits on demand forecasts are proposed to detect when tighter control of processes is necessary. A Monte Carlo supply chain simulation is used to evaluate the performance of these policies under various levels of forecast error and demand variability. Results indicate that several control chart-based policies outperform Intel's current planning policy in terms of cost without significantly increasing variability. The selection of the appropriate policy must be based on the decision-makers' desire to minimize cost compared to the desire to minimize variability, as each policy results in a trade-off between these two objectives.

The nuclear fuel cycle is modelled as a cyclic, multi-stage production-to-inventory system. The objective is to meet a known deterministic demand for energy while minimizing acquisition, production, and inventory holding costs for all stages of the fuel cycle. The model allows for cyclic flow (feedback) of materials, material flow conversion factors at each stage, production lag times at each stage, and for escalating costs of uranium ore. It does not allow shortages to occur in inventories. The model is optimized by the application of the calculus of variations and specifically through recently developed theorems on the solution of functionals constrained by inequalities. The solution is a set of optimal cumulative production trajectories which define the stagewise production rates. Analysis of these production rates reveals the optimal nuclear fuel cycle costs and that inventories (stockpiles) occur in uranium fields, enriched uranium hexafluoride, and fabricated fuel assemblies. An analysis of the sensitivity of the model to variation in three important parameters is performed. / Ph. D.

<p> In this thesis, we focus on the rationing polices for the hotel room inventory control problems. Our study begins with a brief overview of revenue management in hotel industry, emphasizing the importance of room inventory control in revenue management problems. Mathematical models for controlling the room inventory in the literature are then reviewed along with recently developed game theoretic applications in revenue management. In game theoretic context, we establish three types of models to solve the hotel room inventory control problem in three different situations: 1) two-player two-fare-class static single-period game with complete information; 2) two-player two-fare-class dynamic multiple-period game with complete information; and 3) two-player two-fare-class single-period game with incomplete information.</p> <p> In the first situation, we find the existence of unique Nash equilibrium and Stackelberg equilibrium in the non-cooperative case. We provide the exact forms for these equilibria and corresponding conditions. Next, under the dynamic game settings, we provide the sufficient conditions for the unique Nash equilibrium. In the last situation, we consider the static single-period games with incomplete information and discuss the optimal strategies for the uninformed case, secret information case, private information case and public information case. The unique Bayesian Nash equilibrium in each case is found. We then analyze the values of different types of information and study their relations in different situations. Under each game theoretic setting, we present the managerial implications of our solutions along with the numerical examples. The thesis is concluded by a discussion of how game theory can is useful in hotel industry, and its relationship to other topics in revenue management.</p> / Thesis / Doctor of Philosophy (PhD)

In this thesis, we study large-scale dynamic optimization problems in the context of inventory management. We analyze inventory problems with constraints coupling the items or facility locations in the inventory systems, and we propose efficient solutions that are asymptotically optimal or empirically near-optimal. In Chapter 1, we analyze multi-item, single-location inventory systems with storage capacity limits which are formulated as both unconditional expected value constraints and unconditional probability constraints. We first show that problems with unconditional expected value constraints only can be solved to optimality through Lagrangian relaxation. Then, under an assumption on the correlation structure of the demands that is valid under most practical setting, we show that the original problem can be sandwiched between two other problems with expected value constraints only. One of these problems yields a feasible solution to the original problem that is asymptotically optimal as the number of items grows. In Chapter 2, we consider the same problem but with conditional probability constraints, that impose limits on overflow frequency for every possible state in each period. We construct an efficient feasible solution in two steps. First, we solve an unconditional expected value constrained problem with reduced capacity. Second, in each period, given the state information, we solve a single-period convex optimization problem with a conditional expected value constraint. We further show that the heuristic is asymptotically optimal as number of items I grows. In addition, we design another efficient method for moderate values of I, which works empirically well in an extensive numerical study. Moreover, we extract key managerial insights from the numerical study which are critical to decision making in real business problems. In Chapter 3, we analyze single-item, multi-location systems on inventory networks that can be described by directed acyclic graphs (DAG). We propose an innovative reformulation of the problem so that Lagrangian relaxation can still be applied, which, instead of decomposing the problem by facility location, aggregates the state information, leading to a tractable lower bound approximation for the problem. The Lagrange multiplier, which provides information on the value function from the lower bound dynamic program, is used in designing a feasible heuristic. An extensive numerical study is conducted which suggests that both the lower bound approximation and upper bound heuristic perform very well.

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Bakgrund och problemdiskussion: Lagerstyrning är olika aktiviteter som rör hur ett lager hanteras och styrs. Styrningen av ett lager har en stor påverkan på ett företags lönsamhet då det hanterar de aktiviteter som berör lager och därmed också det bundna kapitalet. Lagerstyrning är dock inget som görs i en handvändning, utan det är många delar som ska stämma överens. Lagerstyrningen blir än mer komplex när företag handlar med volatila råvaror. När det kommer till lagerstyrning av produkter med volatila inköpspriser är det viktigt att ta hänsyn till dessa förändringar, för att på så sätt kunna hitta den mest optimala lagerstyrningen. Syfte: Syftet med denna studie är att undersöka vilka konsekvenser som uppstår av att Alutrade inte tar hänsyn till volatila inköpspriser i sin nuvarande lagerstyrning, samt att identifiera vilka lagerstyrningsmetoder, och därmed lagerstyrningspolicy som är lämplig att tillämpa när inköpspriser är volatila för att optimera och uppnå en kostnadseffektiv lageromsättningshastighet. Metod: Uppsatsen behandlas utifrån ett positivistiskt synsätt och ett deduktivt angreppssätt. Uppsatsen har en kvalitativ forskningsmetod men innehåller både kvalitativ och kvantitativ data. Datan har samlats in genom ostrukturerade och semistrukturerade intervjuer, samt mailintervjuer. Resultat: Eftersom Alutrade i dagsläget inte tar så stor hänsyn till de prisförändringar som råder på aluminium marknaden uppstår en del konsekvenser, vilket gör att företagets lagerstyrning påverkas negativt. För att undvika dessa konsekvenser har en lagerstyrningspolicy, som tar hänsyn till volatila inköpspriser, tagits fram. Denna policy utgår från en ABC-klassificering och innehåller lagerstyrningsmetoder såsom modifierad EOQ, beställningspunktsystem vid volatila inköpspriser, säkerhetslager som ett uppskattat antal dagars medelefterfrågan och säkerhetslager beräknat från önskad servicenivå. Med hjälp av den framtagna lagerstyrningspolicyn kan Alutrade undvika konsekvenserna och uppnå de kostnadsbesparingarna som påvisas. / Background: Inventory control is different activities related to how a warehouse is managed. The management of inventory has a big impact on a company's profitability as it manages the activities that concern the inventory and thus has an affect on the tied up capital. However, inventory control is nothing that can be rushed through, since many activities must match. The inventory control becomes even more complex when companies deals with volatile raw materials. When it comes to inventory control of these types of products, it is important to take these changes into account, in order to find the most optimal inventory control. Purpose: The purpose of this thesis is to investigate which consequences that occurs when Alutrade does not take volatile purchase prices into account, furthermore to identify which inventory control methods, and thus inventory control policy, that is suitable to apply when purchase prices are volatile to optimize and achieve a cost-effective inventory turnover. Method: The thesis is based on a positivistic and deductive approach. The study has a qualitative research method but contains both qualitative and quantitative data. The data has been collected through unstructured and semi-structured interviews, as well as mail interviews. Results: As Alutrade currently does not take the price volatility on the aluminum market into much account a number of consequences arise, which means that the company's inventory control is negatively affected. In order to avoid these consequences a inventory control policy, which takes the price volatility into account, has been developed. This policy is based on an ABC classification and contains inventory control methods such as modified EOQ, reorder point system for volatile purchase prices, safety stock as an estimated number of demand days and safety stock calculated from a desired service level. Using the developed inventory control policy, Alutrade can avoid the consequences and achieve the cost savings that are shown.

by Cheung Chi-leung Stanley, Ha Wai-Hung Michael. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 78-79). / ABSTRACT --- p.iii / TABLE OF CONTENTS --- p.iv / LIST OF ILLUSTRATIONS --- p.vi / ACKNOWLEDGMENTS --- p.vii / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Company Background --- p.3 / Objective and Methodology --- p.9 / Chapter II. --- WHAT IS MRP II --- p.12 / Chapter III. --- MRP II SYSTEM IN XYZ COMPANY --- p.15 / Chapter IV. --- THE INVENTORY PROBLEMS --- p.22 / High Level of Excess and No Current Use Inventory --- p.23 / Engineering Changes --- p.23 / Forecast Fluctuation --- p.26 / Customer Order Cancellation --- p.28 / Management Reluctant to Write Off --- p.29 / Long Lead-Time of Components --- p.30 / Active Inventory Level Higher Than Management Expectation --- p.31 / Incorrect Purchase Order Time Bucket --- p.33 / Inefficient Re-scheduling Activities --- p.35 / Inefficient Time Fencing --- p.38 / Ineffective Control --- p.38 / Vendor Early Deliveries --- p.39 / Ineffective Priority of Purchasing Activities --- p.40 / Ineffective Follow-Up of Discrepancies --- p.40 / Unable to Project Inventory Within Tolerance --- p.41 / Alternative Parts --- p.42 / Goods in Transit --- p.48 / Consumption of Active Inventory and Reconciliation of Supply and Demand --- p.49 / Inaccurate Inventory Record --- p.52 / Space Limitation --- p.53 / Staff Training --- p.55 / Policies and Procedures --- p.57 / Cycle Counting --- p.57 / Chapter V. --- SUMMARY OF OBSERVATION --- p.60 / BIBLIOGRAPHY --- p.78