Download or read book Essays in Inventory Decisions Under Uncertainty written by Andrew Steven Manikas and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty is a norm in business decisions. In this research, we focus on the inventory decisions for companies with uncertain customer demands. We first investigate forward buying strategies for single stage inventory decisions. The situation is common in commodity industry where prices often fluctuate significantly from one purchasing opportunity to the next and demands are random. We propose a combined heuristic to determine the optimal number of future periods a firm should purchase at each ordering opportunity in order to maximize total expected profit when there is uncertainty in future demand and future buying price. Second, we study the complexities of bundling of products in an Assemble-To-Order (ATO) environment. We outline a salvage manipulator mechanism that coordinates the decentralized supply chain. Third, we extend our salvage manipulator mechanism to a two stage supply chain with a long cumulative lead time. With significant lead times, the assumption that the suppliers all see the same demand distribution as the retailer cannot be used.

Download or read book Essays on Economic Decisions Under Uncertainty written by Jacques Drèze and published by CUP Archive. This book was released on 1990-05-25 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Professor Dreze is a highly respected mathematical economist and econometrician. This book brings together some of his major contributions to the economic theory of decision making under uncertainty, and also several essays. These include an important essay on 'Decision theory under moral hazard and state dependent preferences' that significantly extends modern theory, and which provides rigorous foundations for subsequent chapters. Topics covered within the theory include decision theory, market allocation and prices, consumer decisions, theory of the firm, labour contracts, and public decisions.

Download or read book Essays on Supply Chain Management with Model Uncertainty written by Mengshi Lu and published by . This book was released on 2014 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditional supply chain management models typically require complete model information, including structural relationships (e.g., how pricing decisions affect customer demand), probabilistic distributions, and parameters. However, in practice, the model information may be uncertain. My dissertation research seeks to address model uncertainty in supply chain management problems using data-driven and robust methods. Incomplete information typically comes in two forms, namely, historical data and partial information. When historical data are available, data-driven methods can be used to obtain decisions directly from data, instead of estimating the model information and then using these estimates to find the optimal solution. When partial information is available, robust methods consider all possible scenarios and make decisions to hedge against the worst-case scenario effectively, instead of making simplified assumptions that could lead to significant loss. Chapter 1 provides an overview of model uncertainty in supply chain management, and discusses the limitations of the traditional methods. The main part of the dissertation is on the application of data-driven and robust methods to three widely-studied supply chain management problems with model uncertainty. Chapter 2 studies the reliable facility location problem where the joint-distribution of facility disruptions is uncertain. For this problem, usually, only partial information in the form of marginal facility disruption probabilities is available. Most existing models require the assumption that the disruptions at different locations are independent of each other. However, in practice, correlated disruptions are widely observed. We present a model that allows disruptions to be correlated with an uncertain joint distribution, and apply distributionally-robust optimization to minimize the expected cost under the worst-case distribution with the given marginal disruption probabilities. The worst-case distribution has a practical interpretation, and its sparse structure allows us to solve the problem efficiently. We find that ignoring disruption correlation could lead to significant loss. The robust method can significantly reduce the regret from model misspecification. It outperforms the traditional approach even under very mild correlation. Most of the benefit of the robust model can be captured at a relatively small cost, which makes it easy to implement in practice. Chapter 3 studies the pricing newsvendor problem where the structural relationship between pricing decisions and customer demand is unknown. Traditional methods for this problem require the selection of a parametric demand model and fitting the model using historical data, while model selection is usually a hard problem in itself. Furthermore, most of the existing literature on pricing requires certain conditions on the demand model, which may not be satisfied by the estimates from data. We present a data-driven approach based only on the historical observations and the basic domain knowledge. The conditional demand distribution is estimated using non-parametric quantile regression with shape constraints. The optimal pricing and inventory decisions are determined numerically using the estimated quantiles. Smoothing and kernelization methods are used to achieve regularization and enhance the performance of the approach. Additional domain knowledge, such as concavity of demand with respect to price, can also be easily incorporated into the approach. Numerical results show that the data-driven approach is able to find close-to-optimal solutions. Smoothing, kernelization, and the incorporation of additional domain knowledge can significantly improve the performance of the approach. Chapter 4 studies inventory management for perishable products where a parameter of the demand distribution is unknown. The traditional separated estimation-optimization approach for this problem has been shown to be suboptimal. To address this issue, an integrated approach called operational statistics has been proposed. We study several important properties of operational statistics. We find that the operational statistics approach is consistent and guaranteed to outperform the traditional approach. We also show that the benefit of using operational statistics is larger when the demand variability is higher. We then generalize the operational statistics approach to the risk-averse newsvendor problem under the conditional value-at-risk (CVaR) criterion. Previous results in operational statistics can be generalized to maximize the expectation of conditional CVaR. In order to model risk-aversion to both the uncertainty in demand sampling and the uncertainty in future demand, we introduce a new criterion called the total CVaR, and find the optimal operational statistic for this new criterion.

Download or read book Inventory Decisions Under Risk and Uncertainty written by Orville Wright Dodson and published by . This book was released on 1965 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays on the Determination of Optimal Inventory Decision Making written by Unchul Yang and published by . This book was released on 1990 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays in Information and Uncertainty written by Qiang Gong and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In the first essay, we analyze how the strategic interaction of firms will affect a firm's decision in disclosing verifiable information. In our model, a firm that is privately informed of market demand will compete with an uninformed rival. When it is common knowledge that the firm is informed and the verifiable disclosure requires no cost, there exists an equilibrium in which the informed firm will fully disclose its information. However, when there is uncertainty about whether the informed firm has received the information or not, then the firm's equilibrium ex-post disclosure strategy will depend on the subsequent competition. We consider quantity-competition with three different timings: the informed firm is a Stackleberg leader; the informed firm is a Stackleberg follower; and the two firms choose quantity output simultaneously (Cournot). We show when the informed firm is a leader, the information will be fully revealed for strategic reasons. When the informed firm is a follower or the two firms make quantity decisions simultaneously, in order to maximize its profit, the informed firm will disclose bad news and withhold the good news to make its competitor less aggressive. In the second essay, we analyze the optimal buy-back contracts for a supplier selling to a retailer when demand is uncertain and when the retailer can take a costly hidden action to forecast demand more accurately. The supplier chooses the wholesale and buy back price to maximize his profits given that the retailer's inventory order level and private information acquisition decisions are both chosen to maximize the retailer's profits. In contrast to the standard buy-back contract model in which the first best of the system can always be implemented, our model suggests that the supplier pays not only the cost of acquiring information, but also the information rent to induce the retailer to invest in acquiring information. In this case, the first best of the system cannot be always implemented. Our model can explain the empirical results that the Vendor Managed Inventory systems are prevalent while the retailer is better informed than the supplier, which cannot be well explained by the standard buy-back contract model.

Download or read book Dynamic Timing Decisions Under Uncertainty written by Nguyen M. Hung and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Jay Forrester's Economic Dynamics was published in 1971 and The Limits to Growth by Dennis Meadows and his associates appeared a year later. The publication of those two books gave rise to twenty years of intense research into the economics of exhaustible resources, research which everywhere has had a substantial impact both on public debate and on academic curricula. And now, just as that line of research is losing steam, economists are focussing on problems associated with the degradation of the natural environment, problems which call for models which, in their formal structure, are quite similar to those already developed in resource economics. This is therefore an appropriate moment for the appearance of a thorough exposition of the economics of exhaustible resources. For that is what Nguyen Manh Hung and Nguyen Van Quyen have provided. Their splendid new book covers equally well the older Hotelling-inspired theory of cake-eating and the economics of search and R&D designed to uncover new and cheaper sources of supply. It provides an entree to the whole subject of resource economics, as well as many new discoveries which will be of interest to experienced researchers.

Download or read book Decision Making Under Uncertainty written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2015-07-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.

Download or read book Risk Uncertainty and Profit written by Frank H. Knight and published by Cosimo, Inc.. This book was released on 2006-11-01 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.

Download or read book Market and Professional Decision making Under Risk and Uncertainty written by Erick Davidson and published by . This book was released on 2007 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: This dissertation explores decision making under risk and uncertainty by professionals and markets composed of professionals. Both essays use empirical data from some of the most competitive economic environments imaginable. The first essay looks at market prices resulting from the sum of both professional and lay choices while the second analyzes the individual choices of professional gamblers. Both essays propose a theoretical framework to not just positively identify what professionals do, but also prescribe normatively what they should do. In both cases, the two are found to be different. The first essay, Market Response to Risk and Uncertainty, 2004 Hurricane Forecasts, develops a simple function to explain insurance losses from hurricanes as a function of short-term forecasts. After demonstrating the accuracy of the function in explaining 2004 insurance claims, the remainder of the essay looks at the stock market's use of these forecasts in pricing insurer and US economy risk. Despite causing billions in damages, both hurricanes and hurricane forecasts are found to have only marginal impacts on financial markets. Surprisingly, markets fail to make efficient use of hurricane forecasts in pricing both insurer and general market exposure to hurricane risk. A potential explanation for market inefficiency around hurricane information is that, like researchers, financial actors may be confounding uncertainty for unpredictability. The second essay, Know When to Hold'em, examines a specific decision within a highly popular, high-stakes version of poker. Like financial markets analyzed in the first essay, professional gamblers must make risky decisions with uncertain probabilities of success. Gamblers are found to be both overly conservative in their choices and overly confident in their abilities to predict uncertain outcomes. A simple statistical model that generalizes across situations to form a naïve probability of having the best cards, is found to be as effective in decision making as players' true expectations of winning. Additionally, a dynamic theoretical model is presented in order to show professional divergence from risk-neutral expected profit maximization in the credit constrained world of tournament poker. Interestingly the value function, derived from this model, is equivalent to an optimal stock price of a poker player.

Download or read book Production Inventory Decisions Under Order Occurence Uncertainty written by John Elden Cleckner and published by . This book was released on 1975 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Three Essays on Production and Inventory Management written by and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of three essays that address issues in production and inventory management. The first essay focuses on inventory management. We study a fixed-reorder-interval, order-up-to (R, nT) inventory replenishment policy in a two-stage serial system with stochastic demand at the lower stage. We develop a simulation based optimization procedure to estimate the long-run average cost and optimal parameter values. The numerical results show that the (R, nT) policy is, on average, 4.4% (5.8%) more expensive than the continuous review (r, nQ) policy (lower bounds). The cost difference is much smaller when the setup cost at the upstream stage and the demand rate are larger. The (R, nT) costs are relatively insensitive to the choice of reorder intervals, T, provided the best corresponding order-up-to level, R, is selected. The second essay deals with production scheduling. We consider the computationally-hard, re-entrant flow, cyclic scheduling problem considered by Graves et al. (1983) and Roundy (1992). We present two problem formulations to minimize job flow time (work-in-process), given a target cycle length (throughput). We describe an efficient optimization method and a new ImproveAlignment (IA) heuristic. Numerical experiments indicate that proposed optimization method was significantly faster than CPLEX-8.0 and solved 40% more test instances to optimality within the specified run time and memory limits. The proposed IA heuristic quickly produced solutions which were, on average, (i) 22% better than those from the Graves' et al. heuristic and (ii) within 14% of the optimal. The third essay focuses on resource planning. We examine a single end-product, discrete-time inventory replenishment problem in a material requirements planning (MRP) environment with demand uncertainty and supply capacity limits on replenishment orders. We develop a simulation-based optimization approach and two novel heuristics. We also evaluate the traditional MRP and safety stock approaches for this problem. Computational experiments show that the two novel heuristics perform very well (on average within 0.06% and 0.66% of optimal, respectively); traditional MRP and safety stock approaches incur higher costs, on average, 45% and 12.05% higher than optimal, respectively. We also provide managerial insights on the effects of different input factors.

Download or read book Judgment Under Uncertainty written by Daniel Kahneman and published by Cambridge University Press. This book was released on 1982-04-30 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thirty-five chapters describe various judgmental heuristics and the biases they produce, not only in laboratory experiments, but in important social, medical, and political situations as well. Most review multiple studies or entire subareas rather than describing single experimental studies.

Download or read book Dissertation Abstracts International written by and published by . This book was released on 2008 with total page 906 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Essays in Derivatives written by Don M. Chance and published by John Wiley & Sons. This book was released on 2011-07-05 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the updated second edition of Don Chance’s well-received Essays in Derivatives, the author once again keeps derivatives simple enough for the beginner, but offers enough in-depth information to satisfy even the most experienced investor. This book provides up-to-date and detailed coverage of various financial products related to derivatives and contains completely new chapters covering subjects that include why derivatives are used, forward and futures pricing, operational risk, and best practices.

Download or read book Essays on Robust Optimization Integrated Inventory and Pricing and Reference Price Effect written by Yuhan Zhang and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of two distinct lines of research e orts. Chapter 2 proposes a general methodology to seek robust solution to multi-stage stochastic optimization problems. Chapters 3, 4 and 5 all deal with models that arise from inventory management and dynamic pricing. Chapter 2 introduces the Extended Affinely Adjustable Robust Counterpart(EAARC). We first propose the general steps of extending affine decision rules via re-parameterizing the uncertainty set, then propose the example of splitting-based EAARC. We show that this approach extends the versatility of affine decision rules beyond what has been proposed by Ben-Tal et al. while retaining tractability. Chapter 3 looks at the classical joint inventory-and-pricing model (single product periodic-review) with concave ordering cost. Concave cost structures may often occur in settings with multiple sources of supply. For this model, assuming additive demand uncertainty, we show that a generalized (s; S; p) policy is optimal under certain conditions imposed on the distribution of the random perturbation. Chapter 4 and 5 focus on the reference price effect in which the price impact on demand is no longer instantaneous, but history-dependent. Chapter 4 analyzes a joint inventory-and-pricing model with reference price e ffect. We prove that a reference price dependent base-stock policy is optimal even though the single period expected pro t may not be concave. In the in finite horizon case, we further show that in the optimal trajectory, reference price converges to a steady state and provide a characterization. Chapter 5 represents some initial e orts in modeling heterogeneity in the consumer group, in which we study a continuous-time dynamic pricing problem under stochastic reference price e ffect. Stochastic optimal control theory is applied to the problem to derive an explicit solution. Various comparative statics are then conducted to benchmark our model against a few simpli ed models.

Download or read book Equilibrium Theory and Applications written by William A. Barnett and published by Cambridge University Press. This book was released on 1991 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Sixth Annual International Symposium in Economic Theory and Econometrics was dedicated to Jacques Drèze on the occasion of his retirement.