bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sequencing to Minimize Work Overload in Assembly Lines with Product Options
Authors: Yano Candace Arai , Rachamadugu Ram 
Published: November 2008

We address the problem of sequencing jobs, each of which is characterized by one of a large number of possible combinations of customer-specified options, on a paced assembly line. These problems arise frequently in the automotive industry. One job must be launched into the system at equal time intervals, where the time interval (or cycle time) is prespecified. The problem is to sequence the jobs to maximize the total amount of work completed, or equivalently, to minimize the total amount of incomplete work (or work overload). Since there is a large number of option combinations, each job is almost unique. This fact precludes the use of existing mixed model assembly line sequencing techniques. We first consider the sequencing problem for a single station which can perform two different sets of operations. We characterize the optimal solution for this problem and use the results as the basis for a heuristic procedure for multiple stations. Computational results with data from a major automobile company are reported.
A Simple Forward Algorithm to Solve General Dynamic Lot Sizing Models with n Periods in 0(n log n) or 0(n) Time
Authors: Federgruen Awi , Tzur Michal 
Published: November 2008

This paper is concerned with the general dynamic lot size model, or (generalized) Wagner-Whitin model. Let n denote the number of periods into which the planning horizon is divided. We describe a simple forward algorithm which solves the general model in 0(n log n) time and 0(n) space, as opposed to the well-known shortest path algorithm advocated over the last 30 years with 0(n2) time. A linear, i.e., 0(n)-time and space algorithm is obtained for two important special cases: (a) models without speculative motives for carrying stock, i.e., where in each interval of time the per unit order cost increases by less than the cost of carrying a unit in stock; (b) models with nondecreasing setup costs. We also derive conditions for the existence of monotone optimal policies and relate these to known (planning horizon and other) results from the literature.
Conflict Management in a Computer-Supported Meeting Environment
Authors: Poole Marshall Scott , Holmes Michael , Desanctis Gerardine 
Published: November 2008

Computer systems to support decision-making, planning, and negotiation in groups have the potential for wide-ranging application. However, knowledge of their effects is sparse, particularly for difficult situations such as group conflict. This study reports a laboratory experiment to examine how a general purpose group decision support system (GDSS) influenced conflict management in small groups making a budget allocation decision. The study tests a model that posits that GDSS impacts on conflict outcomes are mediated by group interaction processes, particularly how the GDSS enters into group interaction. The model posits seven potential impacts—some positive and some negative—that GDSS technology might have on conflict interaction processes. The impacts do not automatically occur, but depend on the nature of the GDSS and how the group applies it. Hence, a given GDSS might result only in a subset of the seven impacts. Among other things, the model predicts that the particular combination of GDSS impacts that materializes differs across groups and that the balance of these impacts, positive or negative, determines positive or negative conflict outcomes. Groups using a particular GDSS, the Software Aided Meeting Management (SAMM) system, were compared to groups using a manual version of the same decision structures built into SAMM and to unsupported groups. Results indicated that there were differences in the level of conflict in SAMM-supported versus manually-supported and unsupported groups, and in conflict management behaviors adopted by the different conditions. Moreover, there were differences in the impacts of SAMM for different groups, and there is some evidence that these contributed to consensus change. Overall, the theoretical model was supported by the study. This model and approach used in this study seem useful for designing future studies concerning the impacts of computer technology on group judgment and choice.
New Bounds for the Identical Parallel Processor Weighted Flow Time Problem
Authors: Webster Scott 
Published: November 2008

In 1964, Eastman, Even, and Isaacs (EEI) presented a polynomial time lower bound for the NP-hard problem of scheduling n jobs on m available and identical processors to minimize weighted flow time. A general bound, of which the EEI bound is a special case, is proposed. Four new bounds for the identical processor problem are given. All of the new bounds can be applied to problems with variable processor ready times. The EEI bound is limited to problems where all processors are initially available at the same time. Two of the four new bounds are shown to dominate the EEI bound. The two other bounds are found to be effective for a particular problem class. Two polynomial time lower bounds for problems with nonidentical processors are introduced. One bound is applicable to the uniform processor problem, the other bound can be applied to the general processor problem. No bounds have previously been proposed for these problems.
File and Work Transfers in Cyclic Queue Systems
Authors: Sarkar D. , Zangwill W. I. 
Published: November 2008

A cyclic queue has one server and n nodes, where each node has its own distinct type of customers that arrive from the outside. The server visits the nodes cyclically, serving the customers first at node 1, then at node 2, and so on through node n, and then repeating from node 1 again. Setup times are incurred when the server switches nodes. Typically, in the past, cyclic queues required that the work at any node arrive from the outside only. Our extension permits special nodes termed dual nodes. At these nodes the total work can include not only the outside customers, but also work transferred from other nodes. The transferred work is attended to as a batch at the dual nodes. Dual nodes permit a number of applications to be modeled including computer file transfer, rework in manufacturing, and internal mail delivery. If there are m dual nodes, the expected waiting time calculation requires solution of a linear system of size n(1 + m) + 2m or less. Often the system size is less, and for a queue with one dual node we prove that a system of only size n is required.
Patterns of Communication Among Marketing, Engineering and Manufacturing—A Comparison Between Two New Product Teams
Authors: Griffin Abbie , Hauser John R. 
Published: November 2008

Models and scientific evidence suggest that firms are more successful at new-product development if there is greater communication among marketing, engineering, and manufacturing. This paper examines communication patterns for two matched product-development teams where the key difference between the groups is that one used a phase-review development process and the other used Quality Function Deployment (QFD), a product-development process adopted recently at over 100 United States and Japanese firms. To our knowledge, this is the first head-to-head comparison of traditional U.S. product development processes with QFD. Our data suggest that QFD enhances communication levels within the core team (marketing, engineering, manufacturing). QFD changes communication patterns from “up-over-down” flows through management to more horizontal routes where core team members communicate directly with one another. On the other hand, the QFD team communicates less on planning information and less with members of the firm external to the team. If this paucity of external communication means that the team has the information it needs for product development, and the QFD process has provided an effective means for moving the information through the team, it is a positive impact of QFD. If the result means that QFD induces team insularity, even when the team needs to reach out to external information sources, it is a cause for concern.
Heuristic Algorithms for the Multiple Depot Vehicle Scheduling Problem
Authors: Dell'Amico Mauro , Fischetti Matteo , Toth Paolo 
Published: November 2008

We consider the NP-hard Multiple Depot Vehicle Scheduling Problem, in which a given set of time-tabled trips have to be assigned to vehicles stationed at different depots, so as to minimize the number of vehicles used and the overall operational cost. The problem arises in the management of transportation companies. In this paper some structural properties of the problem are studied and used to design a new polynomial-time heuristic algorithm which always guarantees the use of the minimum number of vehicles. Several effective refining procedures are also proposed. Extensive computational results on test problems involving up to 1,000 trips and 10 depots are reported, showing that the new approach always produces very tight approximate solutions in small computing times and outperforms other heuristics from the literature.
The Solution of Multiperiod Network Models with Bundle Constraints by Aggregation
Authors: Aderohunmu Rotimi S. , Aronson Jay E. 
Published: November 2008

We present a new network aggregation/disaggregation approach for solving a multiperiod, network model with bundle (Generalized Upper Bounding) side constraints. The model describes production planning and distribution problems. Instead of solving the original multicommodity problem, we transform it so that a pair of single-commodity network flow problems can be solved. The original network is aggregated and the resulting problem is solved. Its solution determines a disaggregated problem that yields a feasible, near optimal solution to the original problem. We describe the determination of theoretical a priori and a posteriori bounds. We also introduce a very tight “computational” error bound. The implementation of the algorithm was tested against MPSX/370, and the specialized code for solving networks with side constraints NETSIDE. The proposed solution method was found to be much more efficient with negligible error.
Decision Structuring with Phantom Alternatives
Authors: Farquhar Peter H. , Pratkanis Anthony R. 
Published: November 2008

A phantom alternative is an illusory choice option—it looks real but for some reason is unavailable at the time a decision is made. Phantoms can both help and hinder successful decision making. On the one hand, phantoms can provide useful information on the boundaries of a decision problem and thus help generate new options through a restructuring of the problem. But phantoms can also produce biases, deception, and suboptimal decisions. We argue that phantoms should be considered explicitly in decision structuring rather than being allowed to work their effects surreptitiously. We offer guidelines on recognizing unavailable alternatives, utilizing the information provided by phantoms, counteracting phantom biases, avoiding deception in decision structuring, and guarding against suboptimal decisions.
A Multiperiod Minimax Resource Allocation Problem with Substitutable Resources
Authors: Nguyen Quynh C. , Stone Richard E. 
Published: November 2008

In this paper we consider a multiperiod resource allocation model in which the resources are storable and substitutable. A specific application of this model relates to the multiperiod production planning for electronic circuit board assembly factories. In this case, resources are electronic components, which are storable, that is, excess components in one period can be used in subsequent periods. Components that can be used in the same function on a circuit board are considered substitutable. Substitutability between components, however, may be dependent upon the specific circuit board on which they reside. Given that there are certain production requirements for the circuit boards, and that some components are in short supply, our algorithm (a) revises the production levels of the affected circuit boards, and (b) efficiently allocates the available components according to the revised production, so as to minimize the maximum weighted deviation from the original production plans. The weights reflect the relative importance of the circuit boards. The objective function uses cumulative production levels and cumulative demands to allow for back-scheduling. We present a primal-dual algorithm that is very efficient. An implementation of the algorithm compares favorably with a standard linear programming code. We solved a problem with 300 components, 20 different circuit boards (average of 10 functions/board) for 10 time periods (approximately 30,000 variables) in less than one minute on a VAX 11/785. We also discuss upper and lower bound extensions, and a lexicographic algorithm to ensure that less critical resources are also allocated effectively.
Communication Networks in Intermediate Markets
Authors: Balderston F. E. 
Published: November 2008

Most commodities move from points of production through successive stages of processing or manufacture and further stages of intermediate distribution before reaching points of final purchase. The final value of a commodity, in fact, is often analyzed by observing the amounts of labor and capital services that are added to it at each of these stages by the firm which owns it at each stage. The setting of the problem is this. Successive stages of dealing in a commodity are in general required on account of any of the following considerations: a) an activity may need to be undertaken at a different scale—i.e., plant size—than that at which a preceding or a succeeding activity needs to be conducted; b) changes in the combinations of commodities may be required from one stage to another; or c) information and contacts need to be mobilized in order to connect disparate groups of actors in the complex of activities.
Cost Horizons and Certainty Equivalents: An Approach to Stochastic Programming of Heating Oil
Authors: Charnes A. , Cooper W. W. , Symonds G. H. 
Published: November 2008

Scheduling heating oil production is an important management problem. It is also a complex one. Weather and demand uncertainties, allocation of production between different refineries, joint- and by-product relations, storage limitations, maintenance of minimal supplies and many other factors need to be considered. This paper is concerned with one of an integrated series of operations research studies directed toward improvement in such scheduling methods. Emphasis is on essentials of the mathematical model. Institutional features and other phases of the OR studies are brought in only as required.
A Network Model to Maximize Navy Personnel Readiness and Its Solution
Authors: Krass Iosif A. , Pinar Mustafa Ç. , Thompson Theodore J. , Zenios Stavros A. 
Published: November 2008

The problem of optimally (re)allocating Navy personnel to combat units is compounded by several considerations: availability of trained personnel, staffing of positions by occupation groups or ranks, and maintaining an acceptable level of readiness. In this paper we model this problem as a nonlinear nondifferentiable optimization problem. A reformulation of the nonlinear optimization problem as a network flow problem is then developed. The formulation results in a network flow problem with side constraints. An additional, nonnetwork, variable measures the readiness level. This new formulation permits the use of network optimization tools in order to solve effectively very large problems. We then develop two numerical methods for solving this problem. One method is based on a heuristic that solves (approximately) the nondifferentiable problem. The second method is based on a Linear-Quadratic Penalty (LQP) algorithm, and it exploits the embedded network structure by placing the side constraints into the objective function. The resulting nonlinear network program is solved using a simplicial decomposition of the network constraint set. Numerical results indicate the viability of this approach on problems with up to 36,000 arcs and 17,000 nodes with 3,700 side constraints.
Incentive Efficient Production Frontiers: An Agency Perspective on DEA
Authors: Bogetoft Peter 
Published: November 2008

In this paper, we examine how empirical production frontiers may contribute to the incentives of production units. We consider a series of Data Envelopment Analysis (DEA) frontiers, and we show when these may be incentive efficient in the sense that they contain all the information that are relevant for optimal incentive provision. The frontiers considered include the so-called constant, decreasing and varying return to scale models, the free disposability and the free replicability models, as well as the increasing and decreasing return to scale models based on a relaxed set of assumptions. Also, we illustrate how to design optimal incentive schemes based on such frontiers. Contents: 1. Introduction, 2. The Incentive Problem, 3. Production Frontiers and Productivity Measures, 4. Incentive Efficient Production Frontiers, 5. Extensions, 6. An Example, 7. Final Remarks, Mathematical Appendix, References.
Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons
Authors: Gallego Guillermo , van Ryzin Garrett 
Published: November 2008

In many industries, managers face the problem of selling a given stock of items by a deadline. We investigate the problem of dynamically pricing such inventories when demand is price sensitive and stochastic and the firm's objective is to maximize expected revenues. Examples that fit this framework include retailers selling fashion and seasonal goods and the travel and leisure industry, which markets space such as seats on airline flights, cabins on vacation cruises, and rooms in hotels that become worthless if not sold by a specific time. We formulate this problem using intensity control and obtain structural monotonicity results for the optimal intensity (resp., price) as a function of the stock level and the length of the horizon. For a particular exponential family of demand functions, we find the optimal pricing policy in closed form. For general demand functions, we find an upper bound on the expected revenue based on analyzing the deterministic version of the problem and use this bound to prove that simple, fixed price policies are asymptotically optimal as the volume of expected sales tends to infinity. Finally, we extend our results to the case where demand is compound Poisson; only a finite number of prices is allowed; the demand rate is time varying; holding costs are incurred and cash flows are discounted; the initial stock is a decision variable; and reordering, overbooking, and random cancellations are allowed.
Optimal Mean-Squared-Error Batch Sizes
Authors: Song Wheyming Tina , Schmeiser Bruce W. 
Published: November 2008

When an estimator of the variance of the sample mean is parameterized by batch size, one approach for selecting batch size is to pursue the minimal mean squared error (mse). We show that the convergence rate of the variance of the sample mean, and the bias of estimators of the variance of the sample mean, asymptotically depend on the data process only through its marginal variance and the sum of the autocorrelations weighted by their absolute lags. Combining these results with variance results of Goldsman and Meketon, we obtain explicit asymptotic approximations for mse, optimal batch size, optimal mse, and robustness for four quadratic-form estimators of the variance of the sample mean. Our empirical results indicate that the asymptotic approximations are reasonably accurate for sample sizes seen in practice. Although we do not discuss batch-size estimation procedures, the empirical results suggest that the explicit asymptotic batch-size approximation, which depends only on a summary measure (which we refer to as the balance point) of the nonnegative-lag autocorrelations, is a reasonable foundation for such procedures.
Asymptotics of Likelihood Ratio Derivative Estimators in Simulations of Highly Reliable Markovian Systems
Authors: Nakayama Marvin K. 
Published: November 2008

We discuss the estimation of derivatives of a performance measure using the likelihood ratio method in simulations of highly reliable Markovian systems. We compare the difficulties of estimating the performance measure and of estimating its partial derivatives with respect to component failure rates as the component failure rates tend to 0 and the component repair rates remain fixed. We first consider the case when the quantities are estimated using naive simulation; i.e., when no variance reduction technique is used. In particular, we prove that in the limit, some of the partial derivatives can be estimated as accurately as the performance measure itself. This result is of particular interest in light of the somewhat pessimistic empirical results others have obtained when applying the likelihood ratio method to other types of systems. However, the result only holds for certain partial derivatives of the performance measure when using naive simulation. More specifically, we can estimate a certain partial derivative with the same relative accuracy as the performance measure if the partial derivative is associated with a component either having one of the largest failure rates or whose failure can trigger a failure transition on one of the “most likely paths to failure.” Also, we develop a simple criterion to determine which partial derivatives will satisfy either of these properties. In particular, we can identify these derivatives using a sensitivity measure which can be calculated for each type of component. We also examine the limiting behavior of the estimates of the performance measure and its derivatives which are obtained when an importance sampling scheme known as balanced failure biasing is used. In particular, we show that the estimates of all derivatives can be improved. In contrast to the situation that arose when using naive simulation, we prove that in the limit, all derivatives can be estimated as accurately as the performance measure when balanced failure biasing is employed. Finally, we formalize the notion of a “most likely path to failure” in the setting of highly reliable Markovian systems. We accomplish this by proving a conditional limit theorem for the distribution of the sample paths leading to a system failure, given that a system failure occurs before the system returns to the state with all components operational. We use this result to establish our other results.
An Experimental Investigation into the Efficacy of Visual Interactive Simulation
Authors: Bell Peter C. , O'Keefe Robert M. 
Published: November 2008

The use of a Visual Interactive Simulation (VIS) model for experimental analysis, where the user initiates runs and gathers information as desired without necessarily any respect for formal analysis, is encouraged by some proponents of VIS and VIS software packages. Proponents of formal output analysis view this approach as dangerous and irresponsible. We designed and executed a laboratory experiment in which 51 subjects solved a case study based around the allocation of trucks in a mining operation in order to investigate the efficacy of VIS to model experimentation. Subjects were provided with a VIS, developed by the authors, which contained a terminating simulation of the system and two different displays: an animation and a dynamically changing histogram. The user could halt execution of the model and change the truck allocation at any time. We found that subjects performed badly relative to a known solution obtained through detailed formal experimentation but performed well compared to solutions they provided prior to use of the model. Use of the animated display was not associated with correct solutions but was associated with more efficient use of the VIS. Subjects who obtained a correct solution investigated fewer alternatives and used fewer interactions than those obtaining incorrect solutions. Finally, we found a significant difference in the process used between subjects providing correct and incorrect solutions.