bluuebunny/crossref_metadata_2025 huggingface dataset:
A Risk-free Perishable Item Returns Policy
Authors: Webster Scott , Weng Z. Kevin
Published: December 2003

A returns policy, which specifies a schedule of rebates from manufacturer to retailer for product left over at the end of the selling season, encourages larger order quantities and can increase manufacturer profit. One downside from a manufacturer's perspective is the possibility of very low profit due to high rebate expense when demand is lower than expected. We take the viewpoint of a manufacturer selling a short life-cycle product to a single risk-neutral retailer and describe returns policies that, when compared to no returns, satisfy two conditions: (1) the retailer's expected profit is increased and (2) the manufacturer's profit is at least as large as when no returns are allowed. We call such a returns policy risk-free.
The Efficiency-Quality Trade-Off of Cross-Trained Workers
Authors: Pinker Edieal J. , Shumsky Robert A.
Published: December 2003

Does cross-training workers allow a firm to achieve economies of scale when there is variability in the content of work, or does it create a workforce that performs many tasks with consistent mediocrity? To address this question we integrate a model of a stochastic service system with models for tenure- and experience-based service quality. When examined in isolation, the service system model confirms a well-known “rule of thumb” from the queueing literature: Flexible or cross-trained servers provide more throughput with fewer workers than specialized servers. However, in the integrated model these economies of scale are tempered by a loss in quality. Given multiple tasks, flexible workers may not gain sufficient experience to provide high-quality service to any one customer, and what is gained in efficiency is lost in quality.

Through a series of numerical experiments we find that low utilization in an all-specialist system can also reduce quality, and therefore the optimal staff mix combines flexible and specialized workers. We also investigate when the performance of the system is sensitive to the staffing configuration choice. For small systems with high learning rates, the optimal staff mix provides significant benefits over either extreme case (a completely specialized or completely flexible workforce). If the system is small and the rate of learning is slow, flexible servers are preferred. For large systems with high learning rates, the model leans toward specialized servers. In a final set of experiments, the model analyzes the design options for an actual call center.
Why Are Forecast Updates Often Disappointing?
Authors: Cattani Kyle , Hausman Warren
Published: December 2003

Demand forecasts do not become consistently more accurate as they are updated. We present examples demonstrating this counterintuitive phenomenon and some theoretical results to explain its occurrence. Specifically, we analyze the effect of demand randomness on forecast-update performance. A surprising result is that under various theoretical models involving demand randomness alone, updated forecasts will be less accurate between 30% and 50% of the time.
Assessing the Value of Information Sharing in a Promotional Retail Environment
Authors: Iyer Ananth. V. , Ye Jianming
Published: December 2003

We focus on a logistics system where inventory is held at three levels: the customers, the retail store, and the warehouse. Retail customer segments are heterogeneous and differ in their reservation prices for product as well as their holding costs. They purchase product from a retail store managed by a retailer. The retailer chooses a retail pricing scheme to maximize his expected profit given a model of customer temporal response to retail pricing. This retailer is supplied product from a warehouse managed by a manufacturer.

The manufacturer is responsible for maintaining inventory level at the warehouse and providing 100% service level for retailer orders. The manufacturer uses all available information to generate an inventory policy that maximizes expected profit subject to the service-level requirement. We evaluate the manufacturer's optimal expected profit under two possible schemes: (1) no information regarding the timing of retail promotion plans, and (2) full information regarding the timing of retail promotion plans.

We show: (1) as the predictability of the sales impact of a promotion decreases, it may be optimal for the retailer to eliminate retail promotions; (2) increased stockpiling tendency of customers increases retailer profits and decreases manufacturer profits; and (3) retail-promotion information sharing can make retail promotions change from being less profitable than no promotions to being more profitable than no promotions for the manufacturer. We show the impact of fitting the model to a grocery store data set that provided data regarding retail sales (and associated prices) of canned tomato soup over two years. We also explore managerial insights suggested by the model.
Requirements Planning with Substitutions: Exploiting Bill-of-Materials Flexibility in Production Planning
Authors: Balakrishnan Anantaram , Geunes Joseph
Published: December 2003

Designing product lines with substitutable components and subassemblies permits companies to offer a broader variety of products while continuing to exploit economies of scale in production and inventory costs. Past research on models incorporating component substitutions focuses on the benefits from reduced safety-stock requirements. This paper addresses a dynamic requirements-planning problem for two-stage multi product manufacturing systems with bill-of-materials flexibility, i.e., with options to use substitute components or subassemblies produced by an upstream stage to meet demand in each period at the downstream stage. We model the problem as an integer program, and describe a dynamic-programming solution method to find the production and substitution quantities that satisfy given multi period downstream demands at minimum total setup, production, conversion, and holding cost. This methodology can serve as a module in requirements-planning systems to plan opportunistic component substitutions based on relative future demands and production costs. Computational results using real data from an aluminum-tube manufacturer show that substitution can save, on average, 8.7% of manufacturing cost. We also apply the model to random problems with a simple product structure to develop insights regarding substitution behavior and impacts.
A Robust Optimization Approach for Improving Service Quality
Authors: Soteriou Andreas C. , Chase Richard B.
Published: December 2003

Delivering high quality service during the service encounter is central to competitive advantage in service organizations. However, achieving such high quality while controlling for costs is a major challenge for service managers. The purpose of this paper is to present an approach for addressing this challenge. The approach entails developing a model linking service process operational variables to service quality metrics to provide guidelines for service resource allocation. The approach enables the service operations manager to take specific actions toward service quality improvement, in light of the costs involved. A novel feature of the approach is the development of robust optimization models, which provide optimal operational guidelines while accounting for uncertainty in the model's parameters. We demonstrate the applicability of the approach in a large health care facility.
The Impact of an Integrated Marketing and Manufacturing Innovation
Authors: Schmidt Glen M. , Porteus Evan L.
Published: December 2003

Suppose you are a Marketing Manager envisioning a new product, or an Operations Manager contemplating a process improvement, or a CEO who commissioned an integrated new product development team. If our assumptions hold, our model offers you a single numerical measure, called the degree of product/process innovation, to determine your initiative's impact on potential sales, prices, market segments, and profits. Our simple, single-period model is a variation of the existing vertically differentiated products model: There are two competing substitute products, and customers will buy at most one of them. Our contribution is to allow new relationships between the valuations of the two products by potential customers, and to allow differing unit production costs. We identify equilibrium results when two competing firms each offer one product, and find the profit maximizing result when one (monopolistic) firm offers both products. The new product infringes on the market in one of two ways: High-end encroachment results when the new product attracts the best customers (those with the highest reservation prices), while low-end encroachment identifies a situation where the new product attracts fringe (lower-end) customers. Low-end encroachment may help explain why an incumbent sometimes fails to recognize the threat of an entrant's product, as we illustrate with an example from the disk drive industry. In short, we offer insight into the value of both a marketing objective (enhancing the product design attributes) and a manufacturing goal (lowering the production cost) in a product and/or process improvement project.
Supply Contract Competition and Sourcing Policies
Authors: Elmaghraby Wedad J.
Published: December 2003

Advances in information technology have opened new venues for companies to create flexible supply chains by offering high-speed communication and tight connectivity. A growing number of companies are taking advantage of new opportunities to outsource portions of their production and other operations. Given the importance of the supplier selection process in the ultimate success of a product, a purchasing manager must understand the different sourcing strategies that she or he can use and the suitability of each sourcing arrangements for her or him. This paper provides an overview of the research that has been done in the fields of operations research and economics on the topic of sourcing strategies. In aggregate, this paper provides a blueprint of what market characteristics can heavily influence a buyer-supplier relationship and, hence, are important to identify and incorporate into the supplier selection process.
Channel Dynamics Under Price and Service Competition
Authors: Tsay Andy A. , Agrawal Narendra
Published: December 2003

This paper studies a distribution system in which a manufacturer supplies a common product to two independent retailers, who in turn use service as well as retail price to directly compete for end customers. We examine the drivers of each firm's strategy, and the consequences for total sales, market share, and profitability. We show that the relative intensity of competition with respect to each competitive dimension plays a key role, as does the degree of cooperation between the retailers. We discover a number of insights concerning the preferences of each party regarding competition. For instance, there will be circumstances under which both retailers would prefer an increase in competitive intensity. Our analysis generalizes existing knowledge about manufacturer wholesale pricing strategies, and rationalizes behaviors that would not be evident without both price and service competition. Finally, we characterize the structure of wholesale pricing mechanisms that can coordinate the system, and show that the most commonly used formats (those that are linear in the order quantity) can achieve coordination only under very limiting conditions.
Impact of Uncertainty and Risk Aversion on Price and Order Quantity in the Newsvendor Problem
Authors: Agrawal Vipul , Seshadri Sridhar
Published: December 2003

We consider a single-period inventory model in which a risk-averse retailer faces uncertain customer demand and makes a purchasing-order-quantity and a selling-price decision with the objective of maximizing expected utility. This problem is similar to the classic newsvendor problem, except: (a) the distribution of demand is a function of the selling price, which is determined by the retailer; and (b) the objective of the retailer is to maximize his/her expected utility. We consider two different ways in which price affects the distribution of demand. In the first model, we assume that a change in price affects the scale of the distribution. In the second model, a change in price only affects the location of the distribution. We present methodology by which this problem with two decision variables can be simplified by reducing it to a problem in a single variable. We show that in comparison to a risk-neutral retailer, a risk-averse retailer in the first model will charge a higher price and order less; where as, in the second model a risk-averse retailer will charge a lower price. The implications of these findings for supply-chain strategy and channel design are discussed. Our research provides a better understanding of retailers' pricing behavior that could lead to improved price contracts and channel-management policies.
Have U.S. Manufacturing Inventories Really Decreased? An Empirical Study
Authors: Rajagopalan S. , Malhotra Arvind
Published: December 2003

Numerous normative models have been developed to determine optimal inventory levels, and several articles and case studies have been written about the concerted efforts and practices adopted by manufacturing firms in the United States to reduce inventories. But little is known about whether inventories have indeed decreased in U.S. manufacturing and whether such a decrease has been restricted to a few well-publicized firms or is true at an industry level. Using data published by the U.S. Census Bureau, the authors study trends in materials, work-in-process, and finished-goods inventory ratios during the period 1961 to 1994 in 20 manufacturing industry sectors and the total U.S. manufacturing sector to determine whether a significant decrease was seen in these ratios. Further, since a great deal of momentum for inventory reduction began in the early 1980s, the authors investigate whether greater improvement was seen in the post-1980 period as compared with the pre-1980 period. We find that material and work-in-process inventories did decrease in a majority of the two-digit industry sectors from 1961 to 1994 and showed greater improvement in about half the sectors in the post-1980 period relative to the pre-1980 period. Finished-goods inventories did decrease in some industry sectors and increase in a few others but did not show a significant trend in more than half the sectors. Total manufacturing inventory ratios decreased from 1961 to 1994 at all three stages—material, work-in-process, and finished goods. However, total manufacturing inventory ratios did not improve at a higher rate during the post-1980 period as compared with the pre-1980 period in any of the three stages. Overall, the analysis provides an encouraging but somewhat mixed picture about the results of U.S. manufacturing inventory-reduction efforts.
Market Segmentation, Advanced Demand Information, and Supply Chain Performance
Authors: Chen Fangruo
Published: December 2003

A monopolist sells a single product to a market where the customers may be enticed to accept a delay as to when their orders are shipped. The enticement is a discounted price for the product. The market consists of several segments with different degrees of aversion to delays. The firm offers a price schedule under which the customers each self-select the price they pay and when their orders are to be shipped. When a customer agrees to wait, the firm gains advanced demand information that can be used to reduce its supply chain costs. This article shows how an optimal pricing-replenishment strategy that balances the costs due to discounted prices and the benefits due to advanced demand information can be determined.
Utilizing Forecast Band Refinement for Capacitated Production Planning
Authors: Kaminsky Philip , Swaminathan Jayashankar M.
Published: December 2003

We present a model for forecast evolution that captures two notions related to forecasts: (1) forecasts are not exact; (2) forecasts over longer horizons are less certain than those over shorter horizons. We model the forecast of discrete demand as a band defined by the lower and upper bounds on demand, such that future forecasts lie within the current band. We develop a capacitated production planning model for a single product with terminal demand. We develop four heuristics for the problem and characterize their performance. In particular, two of the heuristics are optimal for the no holding-cost case. In our computational study, we analyze the performance of our heuristics and compare them to the optimal solution and to a simple heuristic that simulates common industrial practice using point forecasts. We find that two of our heuristics are very close to the optimal solution (less than 0.5% away from optimal on average under the conditions studied). Further, we consider forecast update patterns with primarily early, intermediate, and late information updates and provide insights on the effect of information update patterns on optimal costs.
Creating an Inventory Hedge for Markov-Modulated Poisson Demand: An Application and Model
Authors: Abhyankar Hari S. , Graves Stephen C.
Published: December 2003

Many firms face environments with long manufacturing leadtimes, great product variety, and uncertain, nonstationary demand. A challenge is how to plan production and inventories to provide the best customer service at the least cost. In this paper, we first describe an application at Teradyne in which we implemented an inventory hedge to protect against cyclic demand variability. Based on this experience, we develop a model to better understand the efficacy of this hedging policy. We consider an inventory system for a single aggregate product with a Markov-modulated Poisson demand process. We provide approximate performance measures for this system and develop an optimization problem for determining the size and location of an intermediate-decoupling inventory. We use this optimization to show the value of an intermediate-decoupling inventory as a hedge for cyclic demand environments.
Play It Again, Sam? Optimal Replacement Policies for a Motion Picture Exhibitor
Authors: Swami Sanjeev , Puterman Martin L. , Weinberg Charles B.
Published: December 2003

Every week, motion picture exhibitors must decide whether to keep or replace the movies playing in their theaters in light of the past week's sales data. This decision is complex because of the dynamic decision environment, the uncertainty of demand, the complex revenue-sharing terms between the retailer and the distributor, the need to commit to new movies for several weeks, and the competitive release patterns of movies. We formulate this problem as a Markov Decision Process (MDP) model, using it to obtain replacement policies for the exhibitor. We examine the effect of differences in quality and quantity of available movies, and their respective release dates on the returns from model-based normative solutions. We also show that two practical heuristics are significantly outperformed by the optimal policy for the MDP model. We conclude by applying the model to industry data.
Forecast, Solution, and Rolling Horizons in Operations Management Problems: A Classified Bibliography
Authors: Chand Suresh , Hsu Vernon Ning , Sethi Suresh
Published: December 2003

We present a classified bibliography of the literature in the area of forecast, solution, and rolling horizons primarily in operations management problems. Each one of over 200 selected papers is categorized on five dimensions that identify the horizon type, the model type (deterministic or stochastic), the sources of the horizon, the methods used to obtain horizon results, and the subject area of the paper. The majority of the papers treat dynamic problems in inventory management, production planning, capacity expansion, machine replacement, and warehousing. We discuss the relationship of the horizon results with the theory and practice of rolling-horizon procedures and future research directions.
Optimal and Hierarchical Controls in Dynamic Stochastic Manufacturing Systems: A Survey
Authors: Sethi S. P. , Yan H. , Zhang H. , Zhang Q.
Published: December 2003

Most manufacturing systems are large and complex and operate in an uncertain environment. One approach to managing such systems is that of hierarchical decomposition. This paper reviews the research devoted to proving that a hierarchy based on the frequencies of occurrence of different types of events in the systems results in decisions that are asymptotically optimal as the rates of some events become large compared to those of others. The paper also reviews the research on stochastic optimal control problems associated with manufacturing systems, their dynamic programming equations, existence of solutions of these equations, and verification theorems of optimality for the systems. Manufacturing systems that are addressed include single-machine systems, dynamic flowshops, and dynamic jobshops producing multiple products. These systems may also incorporate random production capacity and demands, and decisions such as production rates, capacity expansion, and promotional campaigns. Related computational results and areas of applications are also presented. A more detailed survey is available at 〈www.utdallas.edu/˜sethi/ITORMS/index.html〉.
Designing a Call Center with Impatient Customers
Authors: Garnett O. , Mandelbaum A. , Reiman M.
Published: December 2003

The most common model to support workforce management of telephone call centers is the M/M/N/B model, in particular its special cases M/M/N (Erlang C, which models out busy signals) and M/M/N/N (Erlang B, disallowing waiting). All of these models lack a central prevalent feature, namely, that impatient customers might decide to leave (abandon) before their service begins.

In this paper, we analyze the simplest abandonment model, in which customers' patience is exponentially distributed and the system's waiting capacity is unlimited (M/M/N + M). Such a model is both rich and analyzable enough to provide information that is practically important for call-center managers. We first outline a method for exact analysis of the M/M/N + M model, that while numerically tractable is not very insightful. We then proceed with an asymptotic analysis of the M/M/N + M model, in a regime that is appropriate for large call centers (many agents, high efficiency, high service level). Guided by the asymptotic behavior, we derive approximations for performance measures and propose “rules of thumb” for the design of large call centers. We thus add support to the growing acknowledgment that insights from diffusion approximations are directly applicable to management practice.
On Throughput Maximization in Constant Travel-Time Robotic Cells
Authors: Dawande Milind , Sriskandarajah Chelliah , Sethi Suresh
Published: December 2003

We consider the problem of scheduling operations in bufferless robotic cells that produce identical parts. The objective is to find a cyclic sequence of robot moves that minimizes the long-run average time to produce a part or, equivalently, maximizes the throughput rate. The robot can be moved in simple cycles that produce one unit or, in more complicated cycles, that produce multiple units. Because one-unit cycles are the easiest to understand, implement, and control, they are widely used in industry. We analyze one-unit cycles for a class of robotic cells called constant travel-time robotic cells. We complete a structural analysis of the class of one-unit cycles and obtain a polynomial time algorithm for finding an optimal one-unit cycle.

Constant travel-time robotic cells are used in real manufacturing operations that the authors have encountered during their interactions with companies. The results and the analysis in this paper offer practitioners (i) a tool to experiment with and study the design of a proposed robotic cell during a prototyping exercise, (ii) a lower bound on the throughput of a robotic cell to help them make an informed assessment of the ultimate productivity level, and (iii) a benchmark throughput level (for comparison purposes) for robotic cells whose operations differ slightly from those discussed in this paper.
Managing Variety for Assembled Products: Modeling Component Systems Sharing
Authors: Ramdas Kamalini , Fisher Marshall , Ulrich Karl
Published: December 2003

Component sharing—using the same version of a component across multiple products—is an approach adopted by many assembled-product manufacturers to achieve high final product variety with lower component variety and cost. This paper presents a methodology for determining which versions of a set of related components should be offered to optimally support a defined finished product portfolio. We develop optimization models that determine which versions of each component should be introduced and which of these versions each product should use to minimize design and production costs. This approach is appropriate for components with a relatively low impact on consumers’ perceptions about product differentiation, which can be shared across a set of products if they meet the most stringent performance requirements in the set. We illustrate our procedure on automotive braking systems, but also discuss its applicability to other components and industries. We identify three conceptually different organizational approaches to component sharing: a coordinated projects approach that requires higher-level organizational echelons above the individual project, a project-by-project approach that does not, and a hybrid partially coordinated approach. We use our model to examine how the gain from the coordinated projects approach relative to the project-by-project approach varies with the number of component versions in consideration, warranty costs, complexity costs, and demand variability. Further, we use our model to highlight the risk of using simplistic heuristics to determine design sequence within a component system in a partially coordinated approach.
Capacity Games in Assembly Systems with Uncertain Demand
Authors: Wang Yunzeng , Gerchak Yigal
Published: December 2003

An assembler needs sets of components, each produced by a different supplier. To produce the components and assemble the final product, the firms involved need to construct their individual production capacities before observing the actual demand. The firms have an incentive scheme (contract) to induce a “proper” capacity build-up. The key parameters of the contract are the set of transfer prices the assembler pays each supplier for a unit of its component. We consider two game settings as to how the terms of the contract are determined. The first is one where the assembler sets the prices, and the second is for the suppliers to simultaneously select the prices each wants to charge for its component.

We first characterize the optimal capacity decision when the system is centralized, and then derive the decentralized equilibrium capacities under each of the two game settings. We show that the decentralized channel performances depend heavily on system structure/parameters. In particular, under the first setting, the performance improves as the assembler's share of the systemwide capacity cost increases and it is not affected by the number of suppliers in the system, while under the second setting, the performance degrades both in the assembler's share of capacity cost and in the number of suppliers. We show that the first setting dominates the second in terms of system performance if and only if the assembler's share of capacity cost is larger than the reciprocal of the number of firms involved.
Probabilistic Service Level Guarantees in Make-to-Stock Manufacturing Systems
Authors: Bertsimas Dimitris , Paschalidis Ioannis Ch.
Published: December 2003

We consider a model of a multiclass make-to-stock manufacturing system. External demand for each product class is met from the available finished goods inventory; unsatisfied demand is backlogged. The objective is to devise a production policy that minimizes inventory costs subject to guaranteeing stockout probabilities to stay bounded above by given constants εj, for each product class j (service level guarantees). Such a policy determines whether the facility should be producing (idling decisions), and if it should, which product class (sequencing decisions). Approximating the original system, we analyze a corresponding fluid model to make sequencing decisions and employ large deviations techniques to make idling ones. We consider both linear and quadratic inventory cost structures to obtain a priority-based and a generalized longest queue first-based production policy, respectively. An important feature of our model is that it accommodates autocorrelated demand and service processes, both critical features of modern failure-prone manufacturing systems.
The National Energy Modeling System: A Large-Scale Energy-Economic Equilibrium Model
Authors: Gabriel Steven A. , Kydes Andy S. , Whitman Peter
Published: December 2003

The National Energy Modeling System (NEMS) is a large-scale mathematical model that computes equilibrium fuel prices and quantities in the U.S. energy sector and is currently in use at the U.S. Department of Energy (DOE). At present, to generate these equilibrium values, NEMS iteratively solves a sequence of linear programs and nonlinear equations. This is a nonlinear Gauss-Seidel approach to arrive at estimates of market equilibrium fuel prices and quantities. In this paper, we present existence and uniqueness results for NEMS-type models based on a nonlinear complementarity/variational inequality problem format. Also, we document mathematically, for the first time, how the inputs and the outputs for each NEMS module link together.
Optimal Design of Truss Structures by Logic-Based Branch and Cut
Authors: Bollapragada S. , Ghattas O. , Hooker J. N.
Published: December 2003

The truss design problem is to find the optimal placement and size of structural bars that can support a given load. The problem is nonlinear and, in the version addressed here, the bars must take certain discrete sizes. It is shown that a logic-based method that dispenses with integer variables and branches directly on logical disjunctions can solve substantially larger problems than mixed integer programming, even though the nonlinearities disappear in the mixed integer model. A primary purpose of the paper is to investigate whether advantages of logic-based branching that have been demonstrated elsewhere for linear problems extend to nonlinear programming.
The Batch Loading and Scheduling Problem
Authors: Dobson Gregory , Nambimadom Ramakrishnan S.
Published: December 2003

This paper discusses the problem of batching and scheduling of certain kinds of batch processors. Examples of these processors include heat treatment facilities, particularly in the steel and ceramics industries, as well as a variety of operations in the manufacture of integrated circuits. In general, for our problem there is a set of jobs waiting to be processed. Each job is associated with a given family and has a weight or delay cost and a volume. The scheduler must organize jobs into batches in which each batch consists of jobs from a single family and in which the total volume of jobs in a batch does not exceed the capacity of the processor. The scheduler must then sequence all the batches. The processing time for a batch depends only on the family and not on the number or the volume of jobs in the batch. The objective is to minimize the mean weighted flow time.

The paper presents an integer programming formulation for this problem, generates a lower bound from a partial LP relaxation, provides a polynomial algorithm to solve a special case, and tests a set of heuristics on the general problem. The ability to pack jobs into batches is the key to efficient solutions and is the basis of the different solution procedures in this paper. The heuristics include a greedy heuristic, a successive knapsack heuristic, and a generalized assignment heuristic. Optimal solutions are obtained by complete enumeration for small problems.

The conclusions of the computational study show that the successive knapsack and generalized assignment heuristics perform better than the greedy. The generalized assignment heuristic does slightly better than the successive knapsack heuristic in some cases, but the latter is substantially faster and more robust. For problems with few jobs, the generalized assignment heuristic and the knapsack heuristic almost always provide optimal solutions. For problems with more jobs, we compare the heruistic solutions' values to lower bounds; the computational work suggests that the heuristics continue to provide solutions that are optimal or close to the optimal. The study also shows that the volume of the job relative to the capacity of the facility and the number of jobs in a family affect the performance of the heuristics, whereas the number of families does not. Finally, we give a worst-case analysis of the greedy heuristic.
Improving Repetitive Manufacturing Systems: Model and Insights
Authors: Webster Scott , Weng Z. Kevin
Published: December 2003

We consider a manufacturing system that is controlled by a fixed-cycle smoothed production policy. This policy, which is becoming increasingly common in repetitive manufacturing environments, is characterized by a production rate that is updated on a periodic basis. We model the system as a stochastic process that includes parameters for vendor responsiveness, plant responsiveness, randomness in production yield rates, nonstationarity and randomness in market demand, demand forecast error, operating cost rates, and safety stock. Properties of the model expose structural relationships between expected system performance and system parameters.
Optimal Policies for Multiechelon Inventory Problems with Markov-Modulated Demand
Authors: Chen Fangruo , Song Jing-Sheng
Published: December 2003

This paper considers a multistage serial inventory system with Markov-modulated demand. Random demand arises at Stage 1, Stage 1 orders from Stage 2, etc., and Stage N orders from an outside supplier with unlimited stock. The demand distribution in each period is determined by the current state of an exogenous Markov chain. Excess demand is backlogged. Linear holding costs are incurred at every stage, and linear backorder costs are incurred at Stage 1. The ordering costs are also linear. The objective is to minimize the long-run average costs in the system. The paper shows that the optimal policy is an echelon base-stock policy with state-dependent order-up-to levels. An efficient algorithm is also provided for determining the optimal base-stock levels. The results can be extended to serial systems in which there is a fixed ordering cost at stage N and to assembly systems with linear ordering costs.
Heavy Traffic Analysis of Dynamic Cyclic Policies: A Unified Treatment of the Single Machine Scheduling Problem
Authors: Markowitz David M. , Wein Lawrence M.
Published: December 2003

This paper examines how setups, due dates, and the mix of standardized and customized products affect the scheduling of a single machine operating in a dynamic and stochastic environment. We restrict ourselves to the class of dynamic cyclic policies, where the machine busy/idle policy and lot-sizing decisions are controlled in a dynamic fashion, but different products must be produced in a fixed sequence. As in earlier work, we conjecture that an averaging principle holds for this queueing system in the heavy traffic limit, and optimize over the class of dynamic cyclic policies. The results allow for a detailed discussion of the interactions between the due-date, setup, and product mix facets of the problem.
Stocking Retail Assortments Under Dynamic Consumer Substitution
Authors: Mahajan Siddharth , van Ryzin Garrett
Published: December 2003

We analyze a single-period, stochastic inventory model (newsboy-like model) in which a sequence of heterogeneous customers dynamically substitute among product variants within a retail assortment when inventory is depleted. The customer choice decisions are based on a natural and classical utility maximization criterion. Faced with such substitution behavior, the retailer must choose initial inventory levels for the assortment to maximize expected profits.

Using a sample path analysis, we analyze structural properties of the expected profit function. We show that, under very general assumptions on the demand process, total sales of each product are concave in their own inventory levels and possess the so-called decreasing differences property, meaning that the marginal value of an additional unit of the given product is decreasing in the inventory levels of all other products. For a continuous relaxation of the problem, we then show, via counterexamples, that the expected profit function is in general not even quasiconcave. Thus, global optimization may be difficult. However, we propose and analyze a stochastic gradient algorithm for the problem, and prove that it converges to a stationary point of the expected profit function under mild conditions. Finally, we apply the algorithm to a set of numerical examples and compare the resulting inventory decisions to those of some simpler, naive heuristics. The examples show that substitution effects can have a significant impact on an assortment's gross profits. The examples also illustrate some systematic distortions in inventory decisions if substitution effects are ignored. In particular, under substitution one should stock relatively more of popular variants and relatively less of unpopular variants than a traditional newsboy analysis indicates.
Multivariate Standardized Time Series for Steady-State Simulation Output Analysis
Authors: Muñoz David F. , Glynn Peter W.
Published: December 2003

The theory of standardized time series, initially proposed to estimate a single steady-state mean from the output of a simulation, is extended to the case where more than one steady-state mean is to be estimated simultaneously. Under mild assumptions on the stochastic process representing the output of the simulation, namely a functional central limit theorem, we obtain asymptotically valid confidence regions for a (multivariate) steady-state mean based on multivariate standardized time series. We provide examples of multivariate standardized time series, including the multivariate versions of the batch means method and Schruben's standardized sum process. Large-sample properties of confidence regions obtained from multivariate standardized time series are discussed. We show that, as in the univariate case, the asymptotic expected volume of confidence regions produced by standardized time series procedures is larger than that obtained from a consistent estimation procedure. We present and discuss experimental results that illustrate our theory.
SMAA-2: Stochastic Multicriteria Acceptability Analysis for Group Decision Making
Authors: Lahdelma Risto , Salminen Pekka
Published: December 2003

Stochastic multicriteria acceptability analysis (SMAA) is a multicriteria decision support method for multiple decision makers in discrete problems. In SMAA, the decision makers need not express their preferences explicitly or implicitly. Instead, the method is based on exploring the weight space in order to describe the valuations that would make each alternative the preferred one. Inaccurate or uncertain criteria values are represented by probability distributions from which the method computes confidence factors describing the reliability of the analysis. In this paper we introduce the SMAA-2 method, which extends the original SMAA by considering all ranks in the analysis. In situations where the “elitistic” SMAA may assess large acceptability only for extreme alternatives without sufficient majority support, the more holistic SMAA-2 analysis can be used to identify good compromise candidates. The results are presented graphically. We consider also situations where partial preference information is available. We demonstrate the new method using a real-life decision problem.
Stochastic Inventory Systems in a Supply Chain with Asymmetric Information: Cycle Stocks, Safety Stocks, and Consignment Stock
Authors: Corbett Charles J.
Published: December 2003

The two critical factors distinguishing inventory management in a multifirm supply-chain context from the more traditional centrally planned perspective are incentive conflicts and information asymmetries. We study the well-known order quantity/reorder point (Q, r) model in a two-player context, using a framework inspired by observations during a case study. We show how traditional allocations of decision rights to supplier and buyer lead to inefficient outcomes, and we use principal-agent models to study the effects of information asymmetries about setup cost and backorder cost, respectively.

We analyze two “opposite” models of contracting on inventory policies. First, we derive the buyer's optimal menu of contracts when the supplier has private information about setup cost, and we show how consignment stock can help reduce the impact of this information asymmetry. Next, we study consignment and assume the supplier cannot observe the buyer's backorder cost. We derive the supplier's optimal menu of contracts on consigned stock level and show that in this case, the supplier effectively has to overcompensate the buyer for the cost of each stockout.

Our theoretical analysis and the case study suggest that consignment stock helps reduce cycle stock by providing the supplier with an additional incentive to decrease batch size, but simultaneously gives the buyer an incentive to increase safety stock by exaggerating backorder costs. This framework immediately points to practical recommendations on how supply-chain incentives should be realigned to overcome existing information asymmetries.
Simultaneous Assignment of Locomotives and Cars to Passenger Trains
Authors: Cordeau Jean-François , Soumis François , Desrosiers Jacques
Published: December 2003

The problem of assigning locomotives and cars to trains is a complex task for most railways. In this paper, we propose a multicommodity network flow-based model for assigning locomotives and cars to trains in the context of passenger transportation. The model has a convenient structure that facilitates the introduction of maintenance constraints, car switching penalties, and substitution possibilities. The large integer programming formulation is solved by a branch-and-bound method that relaxes some of the integrality constraints. At each node of the tree, a mixed-integer problem is solved by a Benders decomposition approach in which the LP relaxations of multicommodity network flow problems are optimized either by the simplex algorithm or by Dantzig-Wolfe decomposition. Some computational refinements, such as the generation of Pareto-optimal cuts, are proposed to improve the performance of the algorithm. Computational experiments performed on two sets of data from a railroad show that the approach can be used to produce optimal solutions to complex problems.
Scheduling with Opting Out: Improving upon Random Priority
Authors: Crès Hervé , Moulin Hervé
Published: December 2003

In a scheduling problem where agents can opt out, we show that the familiar random priority (RP) mechanism can be improved upon by another mechanism dubbed probabilistic serial (PS). Both mechanisms are nonmanipulable in a strong sense, but the latter is Pareto superior to the former and serves a larger (expected) number of agents. The PS equilibrium outcome is easier to compute than the RP outcome; on the other hand, RP is easier to implement than PS. We show that the improvement of PS over RP is significant but small: at most a couple of percentage points in the relative welfare gain and the relative difference in quantity served. Both gains vanish when the number of agents is large; hence both mechanisms can be used as a proxy of each other.
Design for Postponement: A Comprehensive Characterization of Its Benefits Under Unknown Demand Distributions
Authors: Aviv Yossi , Federgruen Awi
Published: December 2003

Recent papers have developed analytical models to explain and quantify the benefits of delayed differentiation and quick response programs. These models assume that while demands in each period are random, they are independent across time and their distribution is perfectly known, i.e., sales forecasts do not need to be updated as time progresses. In this paper, we characterize these benefits in more general settings, where parameters of the demand distributions fail to be known with accuracy or where consecutive demands are correlated. Here it is necessary to revise estimates of the parameters of the demand distributions on the basis of observed demand data. We analyze these systems in a Bayesian framework, assuming that our initial information about the parameters of the demand distributions is characterized via prior distributions. We also characterize the structure of close-to-optimal ordering rules in these systems, for a variety of types of order cost functions.
Inventory Competition Under Dynamic Consumer Choice
Authors: Mahajan Siddharth , van Ryzin Garrett
Published: December 2003

We analyze a model of inventory competition among n firms that provide competing, substitutable goods. Each firm chooses initial inventory levels for their good in a single period (newsboy-like) inventory model. Customers choose dynamically based on current availability, so the inventory levels at one firm affect the demand of all competing firms. This creates a strategic interaction among the firms' inventory decisions.

Our work extends earlier work on variations of this problem by Karjalainen (1992), Lippman and McCardle (1997) and Parlar (1988). Specifically, we model demand in a more realistic way as a stochastic sequence of heterogeneous consumers who choose dynamically from among the available goods (or choose not to purchase) based on a utility maximization criterion. We also use a sample path analysis, so minimal assumptions are imposed on this demand process. We characterize the Nash equilibrium of the resulting stocking game and prove it is unique in the symmetric case. We show there is a bias toward overstocking caused by competition; specifically, reducing the quantity stocked at any equilibrium of the game increases total system profits, and at any joint-optimal set of stocking levels, each firm has an individual incentive to increase its own stock. For the symmetric case, we show that as the number of competing firms increases, the overstocking becomes so severe that total system (and individual firm) profits approach zero. Finally, we propose a stochastic gradient algorithm for computing equilibria and provide several numerical examples.
Real Options in Leasing: The Effect of Idle Time
Authors: Kenyon Chris , Tompaidis Stathis
Published: December 2003

We study options on short-term leases for capital-intensive equipment performing specific functions and services, such as leases for semi-submersible drilling rigs, marine seismic services, corporate real estate leasing, retail space leasing, and apartment leasing. We quantify the effect of an important factor in pricing options on these services: idle time between consecutive lease contracts. We show that while the expected, discounted value for a contract with options is unique, option prices and option exercise prices must be given with respect to a payment structure for the whole contract. We prove that there exist payment schemes in which prices do not depend on exercise probabilities. We use a simple analytic model to derive closed-form solutions for option prices and illustrate our methodology by pricing options for leasing oil-drilling services in the North Sea.