This dissertation consists of three essays on supply chain and revenue management. Its main focus is the integration of dynamic production and demand management decisions for multiple products facing uncertain demand....
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This dissertation consists of three essays on supply chain and revenue management. Its main focus is the integration of dynamic production and demand management decisions for multiple products facing uncertain demand. The study considers three problem settings to inquire into flexibility's influence on a dynamic pricing strategy, managing exogenous demand for intermediary products, and allocation of shared resources among multiple products in a make-to-order environment. The first chapter studies a joint mechanism of dynamic pricing and capacity flexibility to mitigate demand and supply mismatches. We consider a firm producing two substitutable products with price-correlated demands utilizing capacitated product-dedicated and flexible resources. We characterize the structure and sensitivity of the optimal production and pricing decisions and find that the existence of a flexible resource in the firm's capacity portfolio helps maintain stable price differences across items over time. This result has favorable ramifications from a marketing standpoint as it suggests that even when a firm applies a dynamic pricing strategy, it may still establish consistent price positioning among multiple products if it can employ a flexible replenishment resource. We also investigate the economic benefits of a joint strategy versus applying each tool individually. The second chapter considers a setting where a single end-product is assembled from many intermediate components with external demand for the intermediate products as well as the end-product. We address the questions on how to decide on the production quantities for each component, when to initiate an assembly operation and how to set admission rules for demands targeted at various products. In addition to providing structural results for the optimal policy and its sensitivity to product revenues, we also extend the model to multiple customer classes and to settings with partial revenue collecting schemes. We propose a nove
Hybrid Vehicle fuel economy performance is highly sensitive to the "Energy Management" strategy used to regulate power flow among the various energy sources and sinks. Optimal solutions are easy to specify i...
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Hybrid Vehicle fuel economy performance is highly sensitive to the "Energy Management" strategy used to regulate power flow among the various energy sources and sinks. Optimal solutions are easy to specify if the drive cycle is known a priori. It is very challenging to compute controllers that yield good fuel economy for a class of drive cycles representative of typical driver behavior. Additional challenges come in the form of constraints on powertrain activity, like shifting and starting the engine, which are commonly called "drivability" metrics. These constraints can adversely affect fuel economy. In this dissertation, drivability restrictions are included in a Shortest Path stochastic dynamic programming (SPSDP) formulation of the energy management problem to directly address this tradeoff and generate optimal, causal controllers. The controllers are evaluated on Ford Motor Company's highly accurate proprietary vehicle model and compared to a controller developed by Ford for a prototype vehicle. The SPSDP-based controllers improve fuel economy more than 15% compared to the industrial controller on government test cycles. In addition, the SPSDP-based controllers can directly quantify tradeoffs between fuel economy and drivability. Hundreds of thousands of simulations are conducted using real-world drive cycles to evaluate performance and robustness in the real world, demonstrating 10% improvement compared to the baseline. Finally, the controllers are tested in a real vehicle.
The paper considers optimal control of vehicle speed when the vehicle is driven in a particular geographic region with specific terrain and traffic patterns. The vehicle route is assumed to be unknown in advance. The ...
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The paper considers optimal control of vehicle speed when the vehicle is driven in a particular geographic region with specific terrain and traffic patterns. The vehicle route is assumed to be unknown in advance. The properties of the terrain and traffic flow are modeled stochastically. A method is proposed for constructing a control policy off-line to optimally prescribe vehicle speed set-point as a function of current driving conditions, for best on average fuel economy and travel speed performance. A related method is proposed to evaluate expected average fuel economy and travel speed performance of sub-optimal control policies, such as the policies which use constant speed offset relative to average traffic speed. The optimal control law which prescribes vehicle speed set-point can be deployed in advanced vehicle cruise control systems or incorporated into a driver advisory function. In addition, the value function of optimal or suboptimal control policies may be used as a terminal cost in a receding horizon optimization of vehicle speed over routes with known initial segments, or for fuel efficient vehicle routing.
In this paper, we consider a supply contracting problem in which the buyer firm faces non-stationary stochastic price and demand. First, we derive analytical results to compare two pure strategies: (i) periodically pu...
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In this paper, we consider a supply contracting problem in which the buyer firm faces non-stationary stochastic price and demand. First, we derive analytical results to compare two pure strategies: (i) periodically purchasing from the spot market;and (ii) signing a long-term contract with a single supplier. The results from the pure strategies show that the selection of suppliers can be complicated by many parameters, and is particularly affected by price uncertainty. We then develop a stochastic dynamic programming model to incorporate mixed strategies, purchasing commitments and contract cancellations. Computational results show that increases in price (demand) uncertainty favor long-term (short-term) suppliers. By examining the two-way interactions of contract factors (price, demand, purchasing bounds, learning and technology effect, salvage values and contract cancellation), both intuitive and non-intuitive managerial insights in outsourcing strategies are derived. (C) 2008 Published by Elsevier B.V.
In this paper, an approximate dynamicprogramming (ADP) based strategy is applied to the dual adaptive control problem. The ADP strategy provides a computationally amenable way to build a significantly improved policy...
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In this paper, an approximate dynamicprogramming (ADP) based strategy is applied to the dual adaptive control problem. The ADP strategy provides a computationally amenable way to build a significantly improved policy by solving dynamicprogramming on only those points of the hyper-state space sampled during closed-loop Monte Carlo simulations performed under known suboptimal control policies. The potentials of the ADP approach for generating a significantly improved policy are illustrated on an ARX process with unknown/varying parameters. (C) 2009 Elsevier Ltd. All rights reserved.
Water blending is modelled as a combination of a linear program and a stochasticdynamic program. Optimal policies are found for linear and integer-linear formulations using both an expected monetary value and conditi...
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Water blending is modelled as a combination of a linear program and a stochasticdynamic program. Optimal policies are found for linear and integer-linear formulations using both an expected monetary value and conditional value-at-risk criterion. The sensitivity of these solutions to the discretisation over volume and over time is investigated.
We consider a multi-period revenue management problem in which multiple classes of demand arrive over time for the common inventory. The demand classes are differentiated by their revenues and their arrival distributi...
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We consider a multi-period revenue management problem in which multiple classes of demand arrive over time for the common inventory. The demand classes are differentiated by their revenues and their arrival distributions. We investigate monotonicity properties of varying problem parameters on the optimal reward and the policy. (C) 2009 Elsevier B.V. All rights reserved.
Sustainable product lifecycle systems are attracting increasing attention because of cost competition, resource constraints and environmental issues. Short lifecycle products, such as consumer and defense electronics,...
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Sustainable product lifecycle systems are attracting increasing attention because of cost competition, resource constraints and environmental issues. Short lifecycle products, such as consumer and defense electronics, are of particular concern. We formulate a product lifecycle evolution system based on stochastic dynamic programming. By applying the concept of a sustainable product lifecycle system on a product line, conclusions and guidelines for rational decision making can be developed through each phase of the product life cycle. Published by Elsevier B.V.
The production and inventory management of blood products at blood banks and hospitals is it problem of general human interest. As a shortage may put lives at risk, shortages are to be kept to a minimum. As the supply...
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The production and inventory management of blood products at blood banks and hospitals is it problem of general human interest. As a shortage may put lives at risk, shortages are to be kept to a minimum. As the supply is voluntary and costly, any spill of unused blood (products) is also to be minimized. Blood platelets (thrombocytes), which are the most expensive and perishable blood product, have the complication of a limited "shelf life" of only 5-7 days. A general figure in the Western world (the USA and Western Europe) for the spill of blood platelets is in the order of 15-20%. A combined new approach is therefore presented which combines stochastic dynamic programming (SDP) and simulation to provide: (i) Practical simple order-up-to rules that are nearly optimal. (ii) Formal theoretical support. The approach has been applied to a Dutch regional Blood bank. Numerical results show it significant reduction of the figures from: 1%, to 1% for shortages;20% to 1% for spill. A practical question for blood bank managers that still remains is: "How to anticipate irregular production breaks like at Easter and Christmas?" The present paper therefore will extend the combined SDP-Simulation approach to include such breaks. The main findings are: Also for these breaks a simple order-up-to rule remains to be nearly optimal. Also for these breaks the outdating and shortages call be kept less than M. The (stationary) periods with production and the (non-stationary) breaks without can be integrated. The approach thus seems suitable for practical implementation. (C) 2007 Elsevier B.V. All rights reserved.
We seek the minimum harvest age and threshold price for sustaining forest management by constructing a stochastic dynamic programming model using a geometric mean-reverting process for log price dynamics. Three decisi...
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We seek the minimum harvest age and threshold price for sustaining forest management by constructing a stochastic dynamic programming model using a geometric mean-reverting process for log price dynamics. Three decisions-"Wait for harvest", "Harvest & Plant", and "Harvest & Abandon"aEuro"are assumed. The applied growth simulator is deterministic. Using the monthly time series data of sugi (Cryptomeria japonica) log price from 1975 to 2006, our analyses show that when the reverted mean is lower than the cost, the minimum harvest age increases as the current price approaches the threshold price, then declines. In other cases with a higher reverted mean, the minimum harvest age increases as the current or initial log price decreases. When the initial log price approaches the threshold price, the minimum harvest age tends to increase. These phenomena can be used to evaluate the possibility of management abandonment under a stochastic situation of log price dynamics.
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