bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lot Sizing in Serial Assembly Systems with Multiple Constrained Resources
Authors: Harrison Terry P. , Lewis Holly S. 
Published: November 2008

We present a heuristic for lot sizing in serial assembly systems with multiple contrained resources. This procedure, the Coefficient Modification Heuristic (CMH), exploits a special problem structure by solving repetitively a small linear programming restriction of the original problem. The key idea is to modify the constraint coefficients of certain variables in the LP restriction to implicitly account for the capacity consumed in setups. We compare the performance of the CMH with the commercial code, Optimization System Library (OSL), on three families of test problems. The first set is a collation of small-scale random problems that are solved to optimality to provide known benchmarks. The second is a set of problems based on a real printed circuit board manufacturing situation. The third group is a set of medium-scale randomly generated problems based on the underlying structure of the printed circuit board set. Overall, the CMH found solutions that averaged 18% better than time constrained OSL runs in a small fraction of the corresponding CPU times.
A Theory of Cutoff Formation Under Imperfect Information
Authors: Feinberg Fred M. , Huber Joel 
Published: November 2008

Numerous models in the Management Science literature contain constructions that are a variant of the following: A decision-maker must choose from a set of alternatives based on imperfect information as to their relative quality, while further evaluation, through costly, provides more accurate information. We examine decision heuristics in which the optimal search policy entails a screening strategy limiting the number of alternatives in the subsequent, costly evaluation. There are two general methods for accomplishing this screening: Quota cutoffs operate by selecting the optimal number of alternatives to evaluate; Level cutoffs operate by specifying a minimally-acceptable level of the imperfect screening indicator. The present paper has three main objectives. First, to define the Level and Quota cutoff methods, broadly characterize optimal behavior for each and determine what aspects of the decision environment of order statistics as a methodology for exploring decision problems when information is imperfectly known; and third, to discuss the pivotal role of default, or fallback, options in a broad class of search problems. Quota and Level strategies restrict the number of alternatives passing the cutoff-based screen. Because restrictive cutoffs reduce evaluation costs while lowering the expected quality of the item finally selected, changes in the decision environment making the evaluation process less beneficial or increasing its cost drive the optimal cutoff to be more restrictive. In particular, increases in unit evaluation cost, improvement in the quality of a fallback option, decreases in the total number of alternatives available or improvement in the precision of the final evaluation process all lead to more restrictive cutoffs at optimum. These results hold over a remarkably broad range of assumptions and conditions. We also find that a better screening indicator leads to more restrictive screening when evaluation costs are low but, surprisingly, to less restrictive screening when costs are high. Comparing the two strategies, we find the unexpected result that the Quota cutoff strategy is generally superior to the Level, except under on of two fairly uncommon set of circumstances: when evaluation cost is prohibitively high, or when there is a fallback option of very high quality.
A Branch and Bound Procedure for the Resource Constrained Project Scheduling Problem with Discounted Cash Flows
Authors: Icmeli Oya , Erenguc S. Selcuk 
Published: November 2008

Management of projects is complicated by the scarcity of resources required to execute them. Limited resources usually extend the project completion times beyond those determined by CPM/PERT. Several solution procedures have been developed for solving the resource constrained project scheduling problem. One objective commonly used for these problems is to complete the project as early as possible (minimize makespan). The problem considered in this paper is a resource constrained project scheduling problem, with the added features that there are cash flows associated with the project activities, and the objective is to schedule the project activities in such a way that the net present value of cash flows is maximized. With these features the problem becomes financially motivated and more realistic. We introduce a branch and bound procedure to solve the resource constrained project scheduling problem with discounted cash flows. Our procedure exploits the known fact that potential resource violations can be eliminated by introducing additional precedence relations between certain project activities. Specifically, we use the “minimal delaying alternatives” concept to resolve resource conflicts. The bounds in the branch and bound procedure are computed by solving Payment Scheduling Problems, which can be formulated as linear programs and by that are well-solvable. We test our procedure computationally on a set of 90 test problems from the literature and compare it with the only other exact procedure we know of.
Individualized Hybrid Models for Conjoint Analysis
Authors: Green Paul E. , Krieger Abba M. 
Published: November 2008

Increasingly, conjoint analysts are being asked to design and analyze studies involving large numbers of attributes and/or attribute levels. Various types of approaches, including attribute bridging, Adaptive Conjoint Analysis, and hybrid models have been proposed to deal with the problem. This paper describes recent developments in hybrid modeling. Four hybrid models are described and compared in terms of their performance in an industry-based study entailing 15 product attributes. Comparisons are made in terms of internal cross-validation, market share estimates, attribute importances clustering, and its relationship to exogenous background variables. The proposed models are also compared to selected models from the transportation science literature. The authors emphasize the point that comparative model performance may strongly depend on the ways in which the models are to be used.
Option Pricing with Stochastic Volatility: Information-Time vs. Calendar-Time
Authors: Chang Carolyn W. , Chang Jack S. K. 
Published: November 2008

Empirical evidence has shown that subordinated processes represent well the price changes of stocks and futures. Using either transaction counts or trading volume as a proxy for information arrival, it supports the contention that volatility is stochastic in calendar-time because of random information arrival, and thus becomes stationary in information-time. This contention has also been supported later in theoretical models. In this paper we investigate the implication of this contention to option pricing. First we price the option in calendar-time where the return of the underlying asset follows a jump subordinated process. We extend Rubinstein's (Rubinstein, M. 1976. The valuation of uncertain income streams and the valuation of options. Bell J. Econom. Management Sci. 7 407–425.) and Ross's (Ross, S. 1989a. Information and volatility: The no-arbitrage martingale approach to timing and resolution irrelevancy. Finance 44 1–17.) martingale valuation methodology to incorporate the pricing of volatility risk. The resulting equilibrium formula requires estimating seven parameters upon implementation. We then make a stochastic time change, from calendar-time to information-time, in order to obtain a stationary underlying asset return process to price the option. We find that the isomorphic option has random maturity because the number of information arrivals prior to the option's calendar-time expiration date is random. We value the option using Dynkin's (Dynkin, E. B. 1965. Markov Processes, Vols. I and II. Springer-Verlag, Berlin and New York.) version of the Feynman-Kac formula that allows for a random terminal date. The resulting information-time formula requires estimating only one additional parameter compared to the Black-Scholes's in practical application. In this regard, the time change has reduced the computational complexity of the option pricing problem. Simulations show that the formula may outperform the Black-Scholes (Black, F., M. Scholes. 1973. The pricing of options and corporate liabilities. Political Econom. 81 637–659.) and Merton (Merton, Robert C. 1976a. Option pricing when underlying stock returns are discontinuous. Financial Econom. 3 125–143.) models in pricing currency options. As a first attempt to derive valuation relationships in the information-time economy, this investigation may suggest that the information-time approach is a functional alternative to the current calendar-time norm. It is especially suitable for deriving “volatility-free” portfolio insurance strategies.
Eliciting von Neumann-Morgenstern Utilities When Probabilities Are Distorted or Unknown
Authors: Wakker Peter , Deneffe Daniel 
Published: November 2008

This paper proposes a new method, the (gamble-)tradeoff method, for eliciting utilities in decision under risk or uncertainty. The elicitation of utilities, to be used in the expected utility criterion, turns out to be possible even if probabilities are ambiguous or unknown. A disadvantage of the tradeoff method is that a few more questions usually must be asked to clients. Also, the lotteries that are needed are somewhat more complex than in the certainty-equivalent method or in the probability-equivalent method. The major advantage of the tradeoff method is its robustness against probability distortions and misconceptions, which constitute a major cause of violations of expected utility and generate inconsistencies in utility elicitation. Thus the tradeoff method retains full validity under prospect theory, rank-dependent utility, and the combination of the two, i.e., cumulative prospect theory. The tradeoff method is tested for monetary outcomes and for outcomes describing life-duration. We find higher risk aversion for life duration, but the tradeoff method elicits similar curvature of utility. Apparently the higher risk aversion for life duration is due to more pronounced deviations from expected utility.
The Joint Effect of Leadtime Variance and Lot Size in a Parallel Processing Environment
Authors: Song Jing-Sheng , Zipkin Paul H. 
Published: November 2008

We study a basic (r, q) system, in which the demand is a Poisson process and the leadtimes are independent, identically-distributed random variables. The key issue is the joint effect of the leadtime variance and the lot size q on performance. We know that, under a simple base-stock policy (with q = 1), the leadtime variance has no effect at all. We find here that, for larger q, the leadtime variance can have a significant adverse impact on performance. To explore this effect, we test two simple approximations. The simplest ignores the leadtime variance. The second approach is only a bit more complex; it captures the variance effect through a hybrid of two limiting approximations. Both methods provide useful information, but the second is more robust.
Metrics for Managing Research and Development in the Context of the Product Family
Authors: Meyer Marc H. , Tertzakian Peter , Utterback James M. 
Published: November 2008

The paper proposes methods to measure the performance of research and development in new product development. We frame these measures in the context of evolving product families in the technology-based firm. Our goal is to more clearly understand the dynamics of platform renewal and derivative product generation and their consequences for long-term success. We explore the utility of the proposed methods with data gathered from a large measurement systems manufacturer. We find that the methods and measures can help management assess the technological and market leverage achieved from the firm's present and past product platforms. This provides a foundation for transforming single-product, single-period planning processes into a multi-product, multi-period form that embraces the product family and the renewal of product architecture. The research also shows the need to integrate data from engineering, manufacturing, and sales organizations to produce information for managing the growth of the firm's product families.
Decreasing Absolute Risk Aversion and Option Pricing Bounds
Authors: Basso Antonella , Pianca Paolo 
Published: November 2008

In this paper efficient bounds for the price of a call option are obtained using the decreasing absolute risk aversion (DARA) dominance rule. Such lower and upper bounds are obtained minimizing and maximizing, respectively, the objective function of a nonlinear optimization problem. An explicit formula (related to an exponential utility function) is given for the special case of three states of nature. A large number of experiments have been carried out and the numerical results support the conjecture that the same formula holds for problems with a number of states n < 3. Moreover, DARA bounds are more efficient than the bounds obtained using different criteria.
New Product Development Structures and Time-to-Market
Authors: Datar Srikant , Jordan Clark , Kekre Sunder , Rajiv Surendra , Srinivasan Kannan 
Published: November 2008

In fast-cycle, high technology industries, the speed and rate at which companies can introduce products into the market are critical for sustaining competitive advantage and market share. The authors analyze new product development by three international manufacturers that dominate a segment of the electronic component industry. The objective is to examine the impact of two distinct product development strategies and structures on time-to-market. The analysis of more than 200 new product developments provides important findings. A concentrated new product development structure, in contrast to a distributed structure, affords rapid prototyping. However, volume production is reached faster in the distributed structure. Also, devoting more time to prototyping hastens volume production.
The Road to “Root Cause”: Shop-Floor Problem-Solving at Three Auto Assembly Plants
Authors: MacDuffie John Paul 
Published: November 2008

This paper uses case studies of shop-floor problem-solving at three automotive assembly plants to examine organizational influences on process quality improvement. Three complex quality problems—water leaks, paint defects, and electrical defects—were chosen because they are universally found in assembly plants, have multiple sources, and can only be resolved with high levels of interaction and coordination among individuals in multiple departments or functional groups. The case studies focus particularly on the early stages of the problem-solving process—problem definition, problem analysis, and the generation of solutions—emphasizing how each plant tries to identify the “root cause” of defects. The paper then explores consistencies and contrasts within and across the three cases to analyze the factors underlying effective shop-floor problem-solving. Central to this analysis is the idea that successful process quality improvement depends heavily on how the organization influences the cognitive processes of its members. Problem-solving processes benefit from rich data that capture multiple perspectives on a problem, problem categories that are “fuzzy”, and organizational structures that facilitate the development of a common language for discussing problems. Also, when problems are framed as opportunities for learning, the combination of positive attributions that boost motivation and the suppression of threat effects can improve the effectiveness of improvement activities. Finally, when process standardization is understood as marking the beginning (and not the end) of further improvement efforts, the normal inertial tendencies of organizations with respect to adaptive learning can be partially overcome.
A Subpath Ejection Method for the Vehicle Routing Problem
Authors: Rego César 
Published: November 2008

Generically, ejection chains are methods conceived to allow solution transformations to be efficiently carried out by modifying a variable number of their components at each step of a local search algorithm. We consider a subpath ejection chain method for the vehicle routing problem (VRP) under capacity and route length restrictions. The method undertakes the identification of a substructure named the flower reference structure which, besides coordinating moves during an ejection chain construction, allows the creation of neighborhood structures with interesting combinatorial characteristics. Specifically, we base the method on a fundamental property of creating alternating paths and cycles during an ejection chain construction. A new algorithm based on a Tabu search framework is proposed, and computational results on a set of academic and real-world problems indicate that the algorithm may be a good alternative to the best heuristic algorithms for the VRP.
A Multi-Agent Framework for the Coordination and Integration of Information Systems
Authors: Sikora Riyaz , Shaw Michael J. 
Published: November 2008

This paper describes a framework for the coordination and integration of information systems. By modeling typical enterprise information systems as consisting of multiple agents with different functionalities, the methodology provides the representational formalism, coordination mechanisms, and control schemes necessary for integrating heterogeneous units of an information system while meeting such performance criteria as overall effectiveness, efficiency, responsiveness, and robustness. The framework is applied to the development of a manufacturing information system for managing the production processes for making printed circuit boards. Performance results confirm that the system integration framework is important to support complex business processes that involve multiple steps of activities processed by a group of agents across a variety of functionalities.
Research, Development, and Engineering Metrics
Authors: Hauser John R. 
Published: November 2008

We seek to understand how the use of Research, Development, and Engineering (R,D&E) metrics can lead to more effective management of R,D&E. This paper combines qualitative and quantitative research to understand and improve the use of R,D&E metrics. Our research begins with interviews of 43 representative Chief Technical Officers, Chief Executive Offices, and researchers at 10 research-intensive international organizations. These interviews, and an extensive review of the literature, provide qualitative insights. Formal mathematical models attempt to explore these qualitative insights based on more general principles. Our research suggests that metrics-based evaluation and management vary according to the characteristics of the R,D&E activity. For applied projects, we find that project selection can be based on market-outcome metrics when firms use central subsidies to account for short-termism, risk aversion, and scope. With an efficient form of subsidies known as “tin-cupping,” the business units have the incentives to choose the projects that are in the firm's best long-term interests. For core-technological development, longer time delays and more risky programs imply that popular R,D&E effectiveness metrics lead researchers to select programs that are not in the firm's long-term interest. Our analyses suggest that firms moderate such market-outcome metrics by placing a larger weight on metrics that attempt to measure research effort more directly. These metrics include standard measures such as publications, citations, patents, citations to patents, and peer review. For basic research, the issues shift to getting the right people and encouraging a breadth of ideas. Unfortunately, metrics that identify the “best people” based on research success lead directly to “not-invented-here” behaviors. Such behaviors result in research empires that are larger than necessary, but lead to fewer ideas. We suggest that firms use “research tourism” metrics, which encourage researchers to take advantage of research spillovers from universities, other industries, and, even, competitors.
Rational Shopping Behavior and the Option Value of Variable Pricing
Authors: Ho Teck-Hua , Tang Christopher S. , Bell David R. 
Published: November 2008

When a product's price fluctuates at a store, how should rational, cost-minimizing shoppers shop for it? Specifically, how frequently should they visit the store, and how much of the product should they buy when they get there? Would this rational shopping behavior differ across Every Day Low Price (EDLP) and Promotional Pricing (HILO) stores? If shoppers are rational, which retail price format is more profitable, EDLP or HILO? To answer these questions, we develop a normative model that shows how rational customers should shop when the price of the product is random. We derive a closed-form expression for the optimal purchasing policy and show that the optimal quantity to purchase under a given price scenario is linearly decreasing in the difference between the price under that scenario and the average price. This purchase flexibility due to price variability has a direct impact on shopping frequency. Indeed, the benefit of this purchase flexibility can be captured via an “option value” that implicitly reduces the fixed cost associated with each shopping trip. Consequently, rational shoppers should shop more often and buy fewer units per trip when they face higher price variability. Our results suggest that if two stores charge the same average price for a product, rational shoppers incur a lower level of expenditure at the store with a higher price variability. Since stores with different price variabilities coexist in practice, we expect stores with higher price variability to charge a higher average price. Thus, given two stores, a higher relative mean price for a given item should be indicative of higher price variability, and vice versa. These model implications are tested using multicategory scanner panel data from 513 households and pricing data for three stores (two EDLP stores and one HILO store) and 33 product categories over a two-year period. We find strong empirical support for the model implications.
Personnel Tour Scheduling When Starting-Time Restrictions Are Present
Authors: Brusco Michael J. , Jacobs Larry W. 
Published: November 2008

This paper presents an effective solution strategy for an important category of personnel scheduling problems. Specifically, we address the restricted starting-time tour-scheduling problem (RSTP), which involves the determination of the hours of the day (shifts) and days of the week (days on) that employees are assigned to work. RSTP is characterized by restrictions on the number of daily time periods in which employees may begin their shifts. Moreover, the RSTP we consider contains constraints that require separation of starting times. Such restrictions are widely encountered in practice and are based on a number of factors including managerial concerns for control of employee movements, union contractual obligations, and employee preferences for common shift starting times. A two-stage heuristic solution strategy is proposed for RSTP. We developed eight heuristic procedures based on this strategy and applied them to four sets of labor requirements, for each of 27 United Airlines (UA) airport ground stations. One of the best of these procedures yielded solution costs that averaged only 1.36 full-time-equivalent employees above very conservative LP-based lower bounds. Moreover, the solution costs obtained using this procedure were, on average, 28 percent closer to the lower bounds than solution costs obtained using UA's current scheduling system. We conclude that the two-stage heuristic solution strategy is a valuable platform from which to develop procedures for generating near-optimal solutions to this difficult class of personnel scheduling problems.