bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Pit Charging Problem in Steel Production
Authors: Buzacott J. A. , Callahan J. R. 
Published: November 2008

In most integrated works, ingots are used as an intermediate form during the production of steel. These ingots, produced by pouring molten steel into molds, are too large to be used as input for the finishing mills which produce steel products. Hence, more manageable forms (blooms, billets and slabs) are rolled from the ingots by primary mills. The necessity of having uniformly hot steel, provided by a battery of soaking pits, limits the production capacity of any primary mill. At times there is no hot steel and the mill comes into “nothing hot” delays. It is desirable to reduce these delays to a minimum through proper management of the system. One way of doing so is to properly control the charging into the soaking pits of ingots from the queue which builds up there. The paper investigates the properties of this problem which can be considered in two parts. Firstly, when there are ingots of various temperatures in the queue, which should be charged when space becomes available in the pits? Secondly, if space becomes available when there are no hot ingots in the queue, should the empty pit be kept idle waiting for more to arrive or should it be charged with cold ingots which though readily available require considerably longer to prepare for rolling? There is the possibility of inserted idle time. A model is made of the ingot queue-soaking pit-rolling mill system. The properties of the optimal control policy for the ingot queue are investigated using Markov programming. Results are presented which illustrate its complex state dependent nature.
Simplifying the Choice between Uncertain Prospects Where Preference is Nonlinear
Authors: Hammond John S. 
Published: November 2008

This work makes analytical progress in reducing or avoiding two practical difficulties in using preference or utility theory in the analysis of decisions involving uncertainty: (1) assessing the preference curve, and (2) doing calculations with the resultant curve, which may not have an analytically-convenient functional form. The paper identifies circumstances under which simplifications can be found which overcome these difficulties, while at the same time properly reflecting attitude towards risk in the analysis. It is assumed that a decision-maker must choose between risks w̃1 and w̃2. He wishes to make decisions consistent with a preference curve u(·) which exists, but has not necessarily been assessed, so he can choose i to maximize expected preference, Eu(w̃i). Most results require that the cumulative probability distribution of w̃1 and w̃2 cross at most once. The results are widely but not universally applicable. Situations are identified where an easy-to-assess, easy-to-analyze preference curve will serve as a proxy for the decision-maker's own preference curve. These situations permit use of any preferences curve from a class having a specified relationship with the decision-maker's curve. For example, in some instances a negative exponential (constant risk aversion) preference function can be used in place of the decision-maker's curve, and in others an expected value analysis will suffice.
The Researcher and the Manager: A Comparative View of the Need for Mutual Understanding
Authors: Duncan W. Jack 
Published: November 2008

This paper concerns itself with the problem of managerial implementation of scientific research. It employs a survey technique designed to test the manager's and researcher's reactions to propositions developed by Churchman and Schainblatt [Churchman, C. W., A. H. Schainblatt. 1965. The researcher and the manager: A dialectic of implementation. Management Sci. (February) B-16–B-87.], Bennis [Bennis, W. G. 1965. Commentary. Management Sci. (October) B-13–B-16.], and Dyckman [Dyckman, Thomas R. 1967. Management implementation of scientific research: An attitudinal study. Management Sci. (June) B-612–B-619.]. The sample surveyed reflects opinions derived from groups unlike those studied to date. As with previous studies, the results suggest the respondents viewed the implementation issue as a multi-dimensional problem and refused to accept a single position as being the most effective means of obtaining meaningful researcher-manager cooperation. The primary conclusion accentuates both groups' rejection of the separate functions position and advocacy of mutual understanding and provides a general reinforcement of prior investigations. It is suggested that managers and researchers might do well not only to understand their own self-motivation but also to understand the unique problems of implementation faced by both groups. This appreciation would no doubt assist in developing the trust and valid communication necessary for the effective transfer of theory to practice.
A Pattern Recognition Model for Forecasting
Authors: Fogler H. Russell 
Published: November 2008

Corporate planning has been increasingly assisted by advances in the three major areas of economic forecasting: (1) econometric models, (2) time-series analysis, and (3) business cycle indicators. The purpose of this article is to examine the effect of pre-classifying economic observations into more homogeneous groups (“patterns”). It will be shown that the formation of these groups adds further power to our more standard techniques of statistical inference. Early work in pattern recognition began with the development of computer programs for playing chess and checkers. After a brief description of pattern-recognition methodology, a procedure will be presented for pre-classifying economic events into subgroups. Empirical testing and results will be presented, as well as the refinements of this tool for better economic forecasting and planning.
Dynamics of Exponential Smoothing with Trend and Seasonal Terms
Authors: McClain John O. 
Published: November 2008

The characteristics of seasonally adjusted, exponentially smoothed forecasts are studied through the frequency response and impulse response functions. The appropriateness of using exponential smoothing for updating the seasonal base series is called into question, due to its tendency to store random noise for long periods. Exponential smoothing with trend is also examined. It is concluded that Brown's formulation has the property of being critically damped, so that its response to changes in the time series under study is the most rapid possible without overshoot.
A Primal Algorithm to Solve Network Flow Problems with Convex Costs
Authors: Weintraub Andres 
Published: November 2008

The problem of determining continuous flows of minimum cost in a network with convex cost functions is considered. The approach used is that of finding, for any given feasible flow, circuit flows of negative incremental costs. In the main theoretical result of this paper, it is proved that if at each stage, given a feasible nonoptimal flow X, the circuit flow with most negative incremental cost is added to X, linear convergence to the optimal solution will be obtained. In addition, this most negative incremental cost determines an upper bound on the difference in cost between the given feasible solution and the optimal. Based on these concepts, an algorithm, which preserves linear convergence, is presented to determine minimum cost flows in networks with convex costs in the arcs. Results of computer runs made for this algorithm are given. The special case of networks with linear costs is also considered.
Optimal and Heuristic Decisions in Single-and Multi-Item Inventory Systems
Authors: Naddor Eliezer 
Published: November 2008

A comparison of optimal solutions of single-item inventory systems for the three classical policies tZ, sq, and sZ shows that the optimal order levels in the tZ and sZ policies are usually the same, and so are the optimal reorder points in the sq and sZ policies. The total cost for each of the three policies can be expressed as that of a fundamental model using an appropriate equivalent distribution. The fundamental model can be analyzed with ease. It also provides closed-form results for the normal distribution. Heuristic rules are presented allowing the analysis of inventory systems on the basis of their average demand, standard deviation of demand, probability of no demand, lead-time, carrying cost, replenishing cost, and an availability index. Compared with the optimal decisions and costs for identical inventory systems, in which the probability distribution of demand is known, the heuristic rules give excellent results. The optimal and heuristic decisions are extended to multi-item systems in which there is a cost for placing and receiving an order for a family of items every reviewing period. An algorithm is presented for finding the optimal reviewing period and the corresponding decisions and costs. The heuristic decisions compare very favorably with the optimal ones.
Optimal and System Myopic Policies for Multi-Echelon Production/Inventory Assembly Systems
Authors: Schwarz Leroy B. , Schrage Linus 
Published: November 2008

In this paper optimal and near optimal policies are proposed for multi-echelon production/inventory assembly systems under continuous review with constant demand over an infinite planning horizon. Costs at each stage consist of a fixed charge per order or production setup plus a linear holding cost on “echelon” inventory. The objective is minimization of average cost per unit time. The major results of this paper are: a mathematically simple, often optimal, “system myopic” solution, a lower bound on the closeness to optimality of this solution, and a branch and bound algorithm which usually finds the optimal solution quickly.
Economic Optimization of Offshore Petroleum Development
Authors: Frair Les , Devine Mike 
Published: November 2008

Due to shortages in crude oil supplies there is considerable motivation to develop the vast petroleum resources located on our outer continental shelf. Offshore oil operations require great outlays of capital, and this paper presents a model and solution procedure for optimizing the economics of developing a given offshore field. The model considers the following variables: (1) How many offshore drilling platforms are needed? (2) How many wells should be drilled from each platform? (3) What is the location of each platform? (4) From which platform should each well be drilled? (5) What are the time schedules for placing the platforms and drilling the wells? (6) What is the production schedule for each reservoir? The objective of this model is the maximization of discounted after-tax cash flows subject to production limiting constraints. Because of the nonlinear nature and size of this model for realistic problems, it is decomposed into sub-models for which effective solution procedures are developed. Computational results are presented for two example problems.
A Linear Program for Economic Lot Sizes using Labor Priorities
Authors: May J. Gaylord 
Published: November 2008

This paper presents the development of a mathematical model to generate economic lot sizes, on a weekly basis, for an assembly-type shop. The model appears as a linear program which optimizes assigned labor priorities. Included is a description of the results achieved from a successful implementation of the model into the assembly operations. The paper also identifies this shop's problem within the general context of multi-product, multi-period scheduling. In particular, a certain class of scheduling problems is formulated using described techniques.
Marketing Strategy and the Optimal Production Schedule
Authors: Leitch Robert Alan 
Published: November 2008

Incorporation of marketing strategy in production planning can reduce overall costs and significantly increase profits. In this paper a solution procedure similar to the traditional Holt, Modigliani, Muth, and Simon production smoothing model is used to find a combined marketing and production plan in which advertising promotion is utilised to avoid peak-load production costs by shifting seasonal demand for a product. The solution procedure is applicable to a wide variety of market characterizations, and the technique may also be readily adapted to analyse impacts of various aspects of market behavior on the optimal production schedule.
Dispatching from Depot Repair in a Recoverable Item Inventory System: On the Optimality of a Heuristic Rule
Authors: Miller Bruce L. 
Published: November 2008

This paper examines real-time decision rules for a U.S. Air Force inventory system where items are repaired rather than “used up.” The problem is to decide which user in the system has the greatest need for the newly available inventory items coming out of repair. The system is modeled as a Markov decision process and a heuristic rule is presented. This rule, the Transportation Time Look Ahead policy, is justified theoretically by showing that the rule is optimal for a modified model. Thus we have a theoretical justification of a decision rule in a large scale dynamic programming application.
Production Smoothing with Fluctuating Price
Authors: Pekelman Dov 
Published: November 2008

The model presented in this paper deals with a firm facing a known price which varies over time during some finite period [0, T]. The firm wishes to determine the production rate at each instant of that interval which will maximize profit, when adjustment of output incurs additional cost. In the paper we characterize the optimal solution and construct a forward algorithm which is shown to converge to the unique optimal solution. We also specify the conditions for planning and forecast horizons, both of which can be identified by the described algorithm. We use control theory to achieve these results.
Perceptor: A Model for Product Positioning
Authors: Urban Glen L. 
Published: November 2008

A model and measurement methodology is proposed to aid managers in designing new frequently purchased consumer products. The model is structured as a trial and repeat process that produces an estimate of long-run share for a new brand. Physical and psychological product attributes are linked to the trial and repeat probabilities through multidimensional scaling procedures. Perceptual maps of existing brands with ideal brand positionings are derived. The product design determines the new brand's position in the perceptual space, and the distance from the new brand to the ideal brand specifies its probability of purchase. Measurement and estimation procedures are discussed. Predictive and structural tests of the model are reported, and a process for managerial implementation is presented. The outputs of the model are an understanding of the perception, preference, and purchase process, a framework and procedure for measurement, a structure to use in interpreting experimental results, and a tool for estimating the marketing share for alternate new brand designs.
Global Minimization in Nonconvex All-Quadratic Programming
Authors: Reeves Gary R. 
Published: November 2008

This paper describes a branch and bound algorithm for the global minimization of a quadratic objective function subject to quadratic constraints over a bounded interval. No assumptions are made regarding the convexity of either the objective or the constraints. The algorithm consists of three basic steps. First, a local minimum is identified. Next, an interval surrounding this point over which the point is global is determined and eliminated. This interval is determined using linear programming techniques. Finally, bounding convex envelope approximating problems are constructed and solved globally over any remaining intervals. Intervals with bounds greater than the best local minimum objective value are eliminated. Successive iterations of the algorithm take place over the current remaining interval with lowest bound. The algorithm terminates when all intervals have been eliminated. Convergence of the algorithm to a global minimum “within ϵ” in a finite number of iterations is demonstrated. The algorithm has been programmed and tested on a wide range of problems. Computational results have been encouraging. They indicate that for problems tested the algorithm determined a good feasible local minimum rapidly. As problem size increased the majority of time was spent not in determining a local minimum but in verifying that the minimum was global.
A Numerical Algorithm for Recursively-Defined Convolution Integrals Involving Distribution Functions
Authors: Cleroux Robert , McConalogue Denis J. 
Published: November 2008

Reliability studies give rise to families of distribution functions F(n) defined recursively by the repeated convolution of a distribution function F with itself according to the scheme [Formula: see text] where F′ is the derivative of F, and is usually given by a p.d.f. f. In particular, many systems characteristics are defined in terms of integrals of the form ∫0tP(s)(t − x)Q(r)(x) dx where P(s) and Q(r) are the sth and rth members of families generated from distribution functions P and Q, not necessarily distinct. It is seldom possible or convenient to express the F(n) in analytical form. An algorithm based on cubic spline interpolation is given here for recursively generating continuous numerical approximations to the F(n) in a form which allows them to be convoluted together to provide useful approximation to the second of the above integrals.
Improved Linear Integer Programming Formulations of Nonlinear Integer Problems
Authors: Glover Fred 
Published: November 2008

A variety of combinatorial problems (e.g., in capital budgeting, scheduling, allocation) can be expressed as a linear integer programming problem. However, the standard devices for doing this often produce an inordinate number of variables and constraints, putting the problem beyond the practical reach of available integer programming methods. This paper presents new formulation techniques for capturing the essential nonlinearities of the problem of interest, while producing a significantly smaller problem size than the standard techniques.
A Heuristic Adjacent Extreme Point Algorithm for the Fixed Charge Problem
Authors: Walker Warren E. 
Published: November 2008

An algorithm with three variations is presented for the approximate solution of fixed charge problems. Computational experience shows it to be extremely fast and to yield very good solutions. The basic approach is (1) to obtain a local optimum by using the simplex method with a modification of the rule for selection of the variable to enter the basic solution, and (2) once at a local optimum, to search for a better extreme point by jumping over adjacent extreme points to resume iterating two or three extreme points away. This basic approach is the same as that used by Steinberg [Steinberg, D. I. 1970. The fixed charge problem. Naval Res. Log. Quart. 17 217–236.], Cooper [Cooper, L. 1975. The fixed charge problem—I: A new heuristic method. Comp. & Maths, with Appls. 1 89–95.], and Denzler [Denzler, D. R. 1969. An approximate algorithm for the fixed charge problem. Naval Res. Log. Quart. 16 411–416.] in their algorithms, but is an extension and improvement of all three. The algorithm is being used by the U.S Environmental Protection Agency's Office of Solid Waste Management Programs to decide on the number, type, size, and location of the disposal facilities to operate in a region, and how to allocate the region's wastes to these facilities.
An Improved Heuristic Procedure for a Nonlinear Cutting Stock Problem
Authors: Coverdale I. , Wharton F. 
Published: November 2008

Many industries acquire stocks of material in large standard sizes which are then reduced to required widths or lengths according to demand. Scheduling the cutting operations is a particularly difficult problem when a few cutting patterns must be chosen from a vast number of feasible patterns such that the total cost of the reduction process is minimised. Physical constraints and economic considerations restrict the number and type of pattern which can be used. Haessler [Haessiler, R. W. An application of heuristic programming to a nonlinear cutting-stock problem occurring in the paper industry. Unpublished doctoral dissertation, The University of Michigan, Ann Arbor, 1968, available through University Microfilms, Ann Arbor, Dissertation No. 69–12, 119; Haessiler, R. W. 1971. A heuristic programming solution to a nonlinear cutting-stock problem. Management Sci. 17 (12, August) 793–802.] has described a typical problem in the paper industry and a heuristic procedure for obtaining satisfactory schedules. An improved procedure is proposed in which the type of pattern generated and accepted into the schedule is constrained to improve the likelihood that the residual scheduling problem has a feasible and economic solution. Results obtained by the proposed procedure are compared with those obtained manually and by Haessler for a set of eleven actual problems.
Aggregate Planning with Learning Curve Productivity
Authors: Ebert Ronald J. 
Published: November 2008

Research reports of others indicate that many manufacturing organizations experience (a) the probiem of aggregate planning, and (b) experience systematic productivity changes throughout the “life” of a product. Methods for resolving (a) and for quantifying (b) have been developed and applied independently in the operations management literature. All current aggregate planning models are suitable only for constant productivity situations. The current research integrates (a) and (b) into a single computer-based model which permits the development of aggregate-output plans in the face of changing, productivity. The model requires reformulation of traditional aggregate planning methods to incorporate changes in productivity and thereafter solves the reformulated planning problem using direct-computer search. The potential significance of the model is demonstrated by generating a series of aggregate plans for various learning rates. These plans are then used to develop manpower schedules, for cash flow analysis, and for making product pricing decisions.