bluuebunny/crossref_metadata_2025_split huggingface dataset:
Some experiences using MIL‐STD‐105 in the united states air force
Authors: Cocca O. A. 
Published: May 2007

AbstractThe historical and, to some extent, the current role of attribute inspection sampling in the United States Air Force is described. Some insight into consideration culminating in revisions made to the original MIL‐STD‐105 sampling plans is provided. These revisions were motivated from a practitioner's perspective rather than that of a statistical expert. Some significant administrative applications within the Air Force are described, and a practical method, based on the total amount of inspection, is given for distinguishing between sampling plans that have a fixed risk level (i.e., common value on the OC curves).
The effect of nonnormality on variables sampling plans
Authors: Montgomery Douglas C. 
Published: May 2007

AbstractAcceptance sampling plans based on variables have been in use for many years. Recently, there has been a renewal of interest in these plans, because of the relative efficiencies that they offer with respect to attributes sampling regarding sample size. Furthermore, in situations where acceptable quality levels are very small, and a high level of protection is desired, variables sampling is often much more efficient than attributes sampling. An important disadvantage of variables sampling is that the distribution of the parameter being inspected must be known. Most standard variables sampling plans assume that the distribution of this parameter is normal. This article examines the effect of the normality assumption in variables sampling. Methods to detect departures from normality are reviewed.
Some recent findings in bayesian attribute single and double sampling
Authors: Case Kenneth E. , Chen Shao‐Shing 
Published: May 2007

AbstractThis article deals with several items, including theoretical and applied results. Specific topics include (1) a discrete, economically based, attributes acceptance sampling model and its adaptations, (2) relevant costs, (3) relevant prior distributions, (4) comparison of single‐ and double‐sampling results, and (5) reasons for marginal implementation success following excellent implementation efforts. The basic model used is one developed by Guthrie and Johns; adaptations include provisions for fixed costs as well as modifications to permit double sampling. Optimization is exact, rather than approximate. Costs incorporated into the model are for sampling inspection, lot acceptance, and lot rejection. For each of these three categories a fixed cost is included as well as two variable costs, one for each item and the other for each defective item. Discrete prior distributions for the number of defectives in a lot are used exclusively. These include the mixed binomial and Polya distributions. Single‐ and double‐sampling results are compared. Double sampling regularly performs at only slightly lower cost per lot than single sampling. Also, some cost and prior distribution sensitivity results are presented. Comments are provided regarding actual implementation experiences in industry. Practical deficiencies with the Bayesian approach are described, and a recommendation for future research is offered.
Risk preference, multiple attributes, and multiple criteria in bayesian acceptance sampling plans
Authors: Moskowitz Herbert 
Published: May 2007

AbstractAlthough there has been considerable research directed toward developing Bayesian acceptance sampling plans, little consideration has been given to incorporating a decision‐maker's risk attitude or treating such problems in terms of multiple‐type defects and multiple criteria. We review our own work which is focused on the above issues. A model incorporating risk preference is shown to yield substantial differences in the characteristics of an optimal sampling plan relative to a typical Bayesian linear cost (risk neutral) model. Bayesian models and optimization schemes for a variety of multiple‐type defect plans are reviewed. A bicriterion acceptance model, employing average outgoing quality and average inspection cost is also formulated. Traditional versus interactive optimization procedures are compared empirically in terms of ease of use, satisfaction with solutions, and insight gained into the problem.
A minmax search for the critical level of a system: The asymmetric case
Authors: Abigadol Noomi , Ben‐Tal Aharon 
Published: May 2007

AbstractWe consider a system composed ofkcomponents, each of which is subject to failure if temperature is above a critical level. The failure of one component causes the failure of the system as a whole (a serially connected system). Ifziis the critical temperature of theith component thenz*= min{zi: i= 1,2,…,k} is thecritical level of the system. The components may be tested individually at different temperature levels, if the temperature is below the critical level the cost is $1, otherwise the test is destructive and the cost ism> 1 dollars. The purpose of this article is to construct, under a budgetary constraint, an efficient (in a minmax sense) testing procedure which will locate the critical level of the system with maximal accuracy.
Probability bounds on downtimes
Authors: Brockett Patrick L. , Hinich Melvin 
Published: May 2007

AbstractIn this article we consider obtaining probability distributions for total downtime incurred for n units when we have only partial moment information about the downtime distribution per individual failure. Extremal distributions based upon the Markov‐Krein Theorem for Chebychev systems of functions and maximum entropy of distributions are presented.
Tests of independence of continuous random variables which guard against special alternatives
Authors: Weiss Lionel 
Published: May 2007

AbstractFor the problem of testing the independence of a set of continuous random variables, where the test is to be based on n independent and identically distributed observations, tests are constructed that guard against all alternatives but are particularly effective against special alternatives of interest. The tests are based on the numbers of observations falling in the cells of a grid constructed using order statistics.
Easily computed approximations for (s,S) inventory system operating characteristics
Authors: Ehrhardt Richard 
Published: May 2007

AbstractThe operating characteristics of (s,S) inventory systems are often difficult to compute, making systems design and sensitivity analysis tedious and expensive undertakings. This article presents a methodology for simplified sensitivity analysis, and derives approximate expressions for operating characteristics of a simple (s,S) inventory system. The operating characteristics under consideration are the expected values of total cost per period, holding cost per period, replenishment cost per period, backlog cost per period, and backlog frequency. The approximations are obtained by using least‐squares regression to fit simple functions to the operating characteristics of a large number of inventory items with diverse parameter settings. Accuracy to within a few percent of actual values is typical for most approximations. Potential uses of the approximations are illustrated for several idealized design problems, including consolidating demand from several locations, and tradeoffs for increasing service or reducing replenishment delivery lead time.
Penalty calculations and branching rules in a LAV best subset procedure
Authors: Armstrong Ronald D. , Beck P. O. 
Published: May 2007

AbstractLeast absolute value (LAV) regression has become a widely accepted alternative to least squares regression. This has come about as the result of advancements in statistical theory and computational procedures to obtain LAV estimates. Computer codes are currently available to solve a wide range of LAV problems including the best subset regression. The purpose of this article is to study the use of penalty calculations and other branching rules in developing the solution tree for the best subset LAV regression.
Weapon acquisition with target uncertainty
Authors: Nickel Ronald H. , Mangel Marc 
Published: May 2007

AbstractThis article is concerned with choosing a mix of weapons, subject to constraints, when the targets to be attacked are known imprecisely. It is shown that the correct method for optimizing the mix of weapons involves a pair of nested optimization problems (two‐stage optimization). Two methods for optimizing the expected utility of a mix are discussed. The first involves a simultaneous attack model, in which it is implicitly assumed that all weapons are used at once. The second involves a sequential attack model, in which targets appear in random order and are attacked one at a time. Particular attention is given to the question of the appropriate mix of general‐purpose and special‐purpose weapons.
Asymptotic distribution of some multivariate “success run” renewal processes, applied to a 2‐i.i.d. unit repairable system
Authors: Wiens Doug 
Published: May 2007

AbstractIf the probability of “failure” in a multivariate renewal process of the “success run” type is very small, then if certain conditions are imposed on the components of the renewals, the joint distribution of their total durations is approximately exponential with all mass along one line. This result is applied to a 2‐i.i.d. unit repairable system of the “1 out of 2:G, Cold Standby” type.
A (Q,R) inventory model with lost sales and erlang‐distributed lead times
Authors: Buchanan David J. , Love Robert F. 
Published: May 2007

AbstractThe exact expression is derived for the average stationary cost of a (Q,R) inventory system with lost sales, unit Poisson demands, Erlang‐distributed lead times, fixed order cost, fixed cost per unit lost sale, linear holding cost per unit time, and a maximum of one order outstanding. Explicit expressions for the state probabilities and a fast method of calculating them are obtained for the case of Q greater than R. Exponential lead times are analyzed as a special case. A simple cyclic coordinate search procedure is used to locate the minimum cost policy. Examples of the effect of lead time variability on costs are given.
Economic design of X¯ control charts for two manufacturing process models
Authors: Panagos Margaret R. , Heikes Russell G. , Montgomery Douglas C. 
Published: May 2007

AbstractControl charts are widely used for process surveillance. The design of a control chart refers to the choice of sample size, the width of the control limits, and the interval between samples. Economic designs have been widely investigated and shown to be an effective method of determining control chart parameters. This article describes two different manufacturing process models to which the X¯ control chart is applied: The first model assumes that the process continues in operation while searches for the assignable cause are made, and the second assumes that the process must be shut down during the search. Economic models of the control chart for these two manufacturing process models are developed, and the sensitivity of the control chart parameters to the choice of model is explored. It is shown that the choice of the proper manufacturing process model is critical because selection of an inappropriate process model may result in significant economic penalties.
The performance of cannibalization policies in a maintenance system with spares, repair, and resource constraints
Authors: Fisher Warren W. , Brennan J. J. 
Published: May 2007

AbstractThis article presents the results of comparing the performance of several cannibalization policies using a simulation model of a maintenance system with spares, repair, and resource constraints. Although the presence of cannibalization has been incorporated into a number of maintenance system models reported in the literature, the questions of whether cannibalization should be done and what factors affect canibalization have received little attention. Policies tested include both no cannibalization and unlimited cannibalization as well as other based on the number of maintenance personnel available, the short‐term machine failure rate at the time of cannibalization, and the relationship between the mean cannibalization and repair rates. The best policies found are those that allow cannibalization only when it can be done quickly relative to repair or when it can be done without delaying part repair actions. The policy of complete cannibalization (always cannibalize when it is possible) is found to perform poorly except when either average maintenance personnel utilization is very low or when mean cannibalization times are very short relative to mean repair times. The latter result casts doubts on the appropriateness of the assumption of complete cannibalization in many models in the literature.
Estimating normal tail probabilities
Authors: Rukhin Andrew L. 
Published: May 2007

AbstractThe estimation problem of normal tail probabilities is considered. The form of generalized Bayes estimators is derived and the asymptotic behavior of the mean square errors is studied. This study shows that the best unbiased estimator, a formula for which is given, is superior to the maximum likelihoood estimator or to a class of generalized Bayes procedures for large parametric values, but can be significantly improved for moderate values of the parameter.
A Lanchester‐type model of combat with stochastic rates
Authors: Karmeshu  , Jaiswal N. K. 
Published: May 2007

AbstractThe effects of environmental stochasticity in a Lanchester‐type model of combat are investigated. The methodology is based on a study of stochastic differential equations with random parameters characterized by dichotomous Markov processes. Exact expressions for the Laplace transforms of the time evolution of the first‐ and second‐order moments of the system are obtained. A special case when the fluctuations in the parameters occur with great rapidity in comparison with the natural time scale of the system is also analyzed. The stochastic stability in the mean‐square sense is discussed by using the Routh–Hurwitz criterion and it is found that the stochastic perturbations tend to destabilize the system.
Minimal forecast horizon procedures for dynamic lot size models
Authors: Chand Suresh , Morton Thomas E. 
Published: May 2007

AbstractThis article presents new results which should be useful in finding production decisions while solving the dynamic lot sizing problem of Wagner–Whitin on a rolling horizon basis. In a rolling horizon environment, managers obtain decisions for the first period (or the first few periods) by looking at the forecasts for several periods. This article develops procedures to find optimal decisions for any specified number of initial periods (called planning horizon in the article) by using the forecast data for the minimum possible number of future periods. Computational results comparing these procedures with the other procedures reported in the literature are very encouraging.
Tabular aids for fitting weibull moment estimates
Authors: Blischke W. R. , Scheuer E. M. 
Published: May 2007

AbstractMoment estimators for the parameters of the Weibull distribution are considered in the context of analysis of field data. The data available are aggregated, with individual failure times not recorded. In this case, the complexity of the likelihood function argues against the use of maximum‐likelihood estimation, particularly for relatively large sets of data, and moment estimators are a reasonable alternative. In this article, we derive the asymptotic covariance matrix of the moment estimators, and provide listings for BASIC computer programs which generate tables useful for calculation of the estimates as well as for estimating the asymptotic covariance matrix using aggregated data.
Heterogeneous discrete expenditure for diminishing returns
Authors: Hamburger Henry , Slagle James R. 
Published: May 2007

AbstractA probabilistic model is developed that applies to military bombardment, advertising for a mass audience, and other kinds of situations in which striking a target means that less of it is left to strike. The model provides the basis for decision analysis based on marginal gain in such circumstances. Heterogneous resources are considered as well as composite targets. All expenditures are quantized. The model has been developed as part of a computer‐based military expert system, to replace a large complex set of expert opinions. In that application it sharply improves efficiency, yet conforms to major tenets of tactical doctrine.
Use of discounted force arrivals in static force comparisons
Authors: Lorentzen Ralph 
Published: May 2007

AbstractIn traditional static comparisons of two opposing forces, weapons systems on each side are added together after weighting them according to a weapon scoring system. The scoring system does not reflect the availability times of the weapon systems in a perceived conflict. In this paper it is suggested how availability times can be incorporated by introducing the net present value of force arrival patterns. The concept is extended to include the case where uncertainty concerning warning time is reflected through a probability distribution for the time of outbreak of hostilities.
Using simulated annealing to solve routing and location problems
Authors: Golden Bruce L. , Skiscim Christopher C. 
Published: May 2007

AbstractIn recent papers by Kirkpatrick et al., an analogy between the statistical mechanics of large multivariate physical systems and combinatorial optimization has been presented and used to develop a general strategy for solving discrete optimization problems. The method relies on probabilistically accepting intermediate increases in the objective function through a set of user‐controlled parameters. It is argued that by taking such controlled uphill steps, from time to time, a high quality solution can eventually be found in a moderate amount of computer time. In this paper, we implement this idea, apply it to the traveling salesman problem and the p‐median location problem, and test the approach extensively.
A stochastic network formulation for complex sequential processes
Authors: Lemoine Austin J. 
Published: May 2007

AbstractA network model incorporating stochastic features is considered. The model represents a complex sequential process where an object or system moves through a succession of states (nodes) and operating modes (classes) in the course of carrying out its function (fulfilling its purpose). Transitions between states and operating modes occur in a possibly random manner and require (consume) some resource in randomly varying amounts. We discuss the routing behavior and resource requirements of a typical object as it moves through (and eventually out of) the network. We then shift our focus from a single object and its odyssey to the network as a whole, where time is the resource and many objects are entering the network according to a possibly nonhomogeneous Poisson pattern; in this vein, we discuss the evolution of the network over time. Finally, we consider some applications of the formulation, and results.
A forward network simplex algorithm for solving multiperiod network flow problems
Authors: Aronson Jay E. , David Chen B. 
Published: May 2007

AbstractAn optimization model which is frequently used to assist decision makers in the areas of resource scheduling, planning, and distribution is the minimum cost multiperiod network flow problem. This model describes network structure decision‐making problems over time. Such problems arise in the areas of production/distribution systems, economic planning, communication systems, material handling systems, traffic systems, railway systems, building evacuation systems, energy systems, as well as in many others. Although existing network solution techniques are efficient, there are still limitations to the size of problems that can be solved. To date, only a few researchers have taken the multiperiod structure into consideration in devising efficient solution methods. Standard network codes are usually used because of their availability and perceived efficiency. In this paper we discuss the development, implementation, and computational testing of a new technique, the forward network simplex method, for solving linear, minimum cost, multiperiod network flow problems. The forward network simplex method is a forward algorithm which exploits the natural decomposition of multiperiod network problems by limiting its pivoting activity. A forward algorithm is an approach to solving dynamic problems by solving successively longer finite subproblems, terminating when a stopping rule can be invoked or a decision horizon found. Such procedures are available for a large number of special structure models. Here we describe the specialization of the forward simplex method of Aronson, Morton, and Thompson to solving multiperiod network network flow problems. Computational results indicate that both the solution time and pivot count are linear in the number of periods. For standard network optimization codes, which do not exploit the multiperiod structure, the pivot count is linear in the number of periods; however, the solution time is quadratic.
On a large sample test for the traffic intensity in GI|G|s queue
Authors: Subba Rao S. , Harishchandra K. 
Published: May 2007

AbstractA large sample test based on normal approximation for the traffic intensity parameter ρ in the cases of single and multiple‐server queues has been proposed. The test procedure is developed without imposing steady‐state assumptions and is applicable to queueing systems with general interarrival and service‐time distributions.
A note on the single‐machine scheduling problem with minimum weighted completion time and maximum allowable tardiness
Authors: Chand Suresh , Schneeberger Hans 
Published: May 2007

AbstractThis paper analyzes the Smith‐heuristic for the single‐machine scheduling problem where the objective is to minimize the total weighted completion time subject to the constraint that the tradiness for any job does not exceed a prespecified maximum allowable tardiness. We identify several cases of this problem for which the Smith‐heuristic is guaranteed to lead to optimal solutions. We also provide a worst‐case analysis of the Smith‐heuristic; the analysis shows that the fractional increase in the objective function value for the Smith‐heuristic from the optimal solution is unbounded in the worst case.
The matrix game derived from the many‐against‐many battle
Authors: Kikuta Kensaku 
Published: May 2007

AbstractThe many‐against‐many battle, which is a variant of the Friedman's one‐against‐many battle, is formulated as a two‐person constant‐sum game. It is shown that the matrix which expresses this game has a saddle point. Some cases are presented in which the payoff matrix of the game can be reduced. Finally, some parametrically special cases are analyzed.
The procurement problem: An integer programming problem well suited to a solution using duality
Authors: Gunn Eldon A. , Kusiak Andrew 
Published: May 2007

AbstractA procurement problem, as formulated by Murty [10], is that of determining how many pieces of equipment units of each of m types are to be purchased and how this equipment is to be distributed among n stations so as to maximize profit, subject to a budget constraint. We have considered a generalization of Murty's procurement problem and developed an approach using duality to exploit the special structure of this problem. By using our dual approach on Murty's original problem, we have been able to solve large problems (1840 integer variables) with very modest computational effort. The main feature of our approach is the idea of using the current evaluation of the dual problem to produce a good feasible solution to the primal problem. In turn, the availability of good feasible solutions to the primal makes it possible to use a very simple subgradient algorithm to solve the dual effectively.