|Copy reference link||DOI: 10.1111/poms.12173|
Abstract: The manufacturing complexity of many high-tech products results in a substantial variation in the quality of the units produced. After manufacturing, the units are classified into vertically differentiated products. These products are typically obtained in uncontrollable fractions, leading to mismatches between their demand and supply. We focus on product stockouts due to the supply–demand mismatches. Existing literature suggests that when faced with product stockouts, firms should satisfy all unmet demand of a low-end product by downgrading excess units of a high-end product (downward substitution). However, this policy may be suboptimal if it is likely that low-end customers will substitute with a higher quality product and pay the higher price (upward substitution). In this study, we investigate whether and how much downward substitution firms should perform. We also investigate whether and how much low-end inventory firms should withhold to strategically divert some low-end demand to the high-end product. We first establish the existence of regions of co-production technology and willingness of customers to substitute upward where firms adopt different substitution/withholding strategies. Then, we develop a managerial framework to determine the optimal selling strategy during the life cycle of technology products as profit margins shrink, manufacturing technology improves, and more capacity becomes available. Consistent trends exist for exogenous and endogenous prices.
|Copy reference link||DOI: 10.1016/j.ijpe.2010.06.018|
Abstract: We study a problem of dynamic quantity competition in continuous time with two competing retailers facing different replenishment cost structures. Retailer 1 faces fixed ordering costs and variable procurement costs and all inventory kept in stock is subject to holding costs. Retailer 2 only faces variable procurement costs. Both retailers are allowed to change their sales quantities dynamically over time. Following the structure of the economic order quantity (EOQ) model, retailer 1 places replenishment orders in batches and retailer 2 follows a just-in-time (JIT) policy. The objective of both retailers is to maximize their individual average profit anticipating the competitor's replenishment and output decisions. The problem is solved by a two-stage hierarchical optimization approach using backwards induction. The second-stage model is a differential game in output quantities between the two retailers for a given cycle length. At the first stage, the replenishment policy is determined. We prove the existence of a unique optimal solution and derive an open-loop Nash equilibrium. We show that both retailers follow contrary output strategies over the order cycle. The EOQ retailer, driven by inventory holding costs, decreases his market share whereas the output of the JIT retailer increases. Moreover, depending on the cost structure, the EOQ retailer might partially be a monopolist. At the first stage, the EOQ retailer determines the cycle length, anticipating the optimal output trajectories at the second stage.
|Copy reference link||DOI: 10.1080/00207543.2010.532910|
Abstract: Tailored for a complex application in the process industry, this article examines a multi-product production planning and scheduling problem with sequence-dependent setup cost and times. The manufacturing process is characterised by a two-stage structure where the sequencing problem occurs on the first level and contribution margin, holding cost, penalty cost are accounted on the second level. We present a hybrid mixed-binary optimisation model based on the general lot-sizing and scheduling problem [Fleischmann, B. and Meyr, H. 1997. The general lotsizing and scheduling problem. OR Spectrum, 19 (1), 11–21], which combines discrete and continuous-time elements within a standard inventory and lot-size (I&L) formulation. Since the I&L formulation does not provide sharp linear programming-relaxation bounds, we present two alternative reformulations based on a transportation problem. In a numerical study inspired by real industry data, we show that on average, both reformulations yield significant improvements in computation time and integrality gap.
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Abstract: We consider an economic order quantity model where the supplier offers an all-units quantity discount and a price sensitive customer demand. We compare a decentralized decision framework where selling price and replenishment policy are determined independently to simultaneous decision making. Constant and dynamic pricing are distinguished. We derive structural properties and developalgorithms that determine the optimal pricing and replenishment policy and show how quantity discounts not only influence the purchasing strategy but also the pricing policy. A sensitivity analysis indicates the impact of the fixed-holding cost ratio, the discount policy, and the customers' price sensitivity on the optimal decisions.
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Abstract: The goal matching supply with demand, which is the fundament of supply chain management, has changed the role of operations management from pure cost control to value creation. The recent developments of integrating revenue management with supply chain management activities and the resulting successes have indicated the tremendous potential to improve the supply chain performance in the same way that revenue management has revolutionized the airline industry. This thesis investigates how an integration of revenue management and supply chain management influences decision making and the overall profitability. In particular, simultaneous decision making of selling price, inventory control strategy and capacity acquisition is analyzed.
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Abstract: In disassemble-to-order (DTO) systems randomness of recoverable parts gained from used products creates a major challenge for appropriate planning. Typically, it is assumed that yields from disassembly are either stochastically proportional (SP) or follow a binomial (BI) process. In the case of yield misspecification, it can be shown that the BI yield assumption usually results in a lower penalty than the SP yield assumption. For BI yield, however, a suitable, powerful heuristic is needed in order to facilitate DTO problems olving for complex realworld product structures. We present a heuristic approach that is based on a ecomposition procedure for the underlying non-linear stochastic optimization problem and that can be applied to problems of arbitrary size. A numerical performance study reveals that this heuristic yields close - to - optimal results.
Prof. Dr. Sandra Transchel
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