On a generalized $L_2$ projection and some related stability estimates in Sobolev spaces

Summary. In this paper we investigate a stability estimate needed in hybrid finite and boundary element methods, especially in hybrid coupled domain decomposition methods including mortar finite elements. This stability estimate is equivalent to the stability of a generalized projection in certain Sobolev spaces. Using piecewise linear trial spaces and appropriate piecewise constant test spaces, the stability of the generalized projection is proved assuming some mesh conditions locally. Received April 11, 2000 / Revised version received February 15, 2001 / Published online July 25, 2001     

The Most Critical Path in a PERT Network

The classical PERT approach uses the path with the largest expected duration as the critical path to estimate the probability of completing a project by a given deadline. However, in general, such a path is not the ‘most critical’ path and does not provide the smallest estimate for the probability of completion time. This paper studies the ‘most critical path’ problem and formulates it as an optimal path problem in a deterministic network with a two-attribute fractional objective function. An exact solution approach is presented for the optimal path problem which also gives the solution to the most critical path problem. The illustrative examples as well as our computational results demonstrate that the proposed algorithm provides estimates for the probabilities of completion time that are much more accurate than those of the classical approach.     

Conflict Analysis in the Politico-Military Environment of a New World Order

A methodology is developed to analyse present and future crisis and conflict potentials of small or large geopolitical regions. A set of criteria is used to describe the present economic, social, political and military conditions of a country and the future criteria trends. A multi-criteria decision analysis model is invoked to compute the crisis and conflict potentials under simultaneous consideration of all other countries in that region. The methodology is demonstrated in the crisis and conflict potentials analysis of the former Soviet republics including bordering countries.     

Structure of fullerene-containing soot at different formation stages of arc discharge vaporization of graphite

Electron microscopy is used in a study of nanoclusters of the carbon soot deposited on a probe in different areas of arc discharge during graphite vaporization under conditions favorable for fullerene synthesis. It is found that the spatial network of soot nanoclusters consists of alternating regions of higher density or associates of carbon particles. Two types of nanoclusters have been identified with the correlation radii of the associates equal to 0.6–0.8 and 1.6–2.2 nm, respectively. Type I nanoclusters are dominant in the soot microparticles, and their structure shows practically no variations with increasing separation r of the soot collector from the discharge axis over the range of distances studied, r=1–9 cm. The effective radius R ₀ of the “elementary” particles making up the associates in the soot nanoclusters of Type I calculated with the use of scaling relationships is 0.15–0.17 nm and is close to the gas-kinetic radius of carbon atoms. Type II nanoclusters have been identified in soot collected at r>3 cm. Values of R ₀ calculated in this case are 0.6–0.9 nm and decrease with increasing r, which indicates the presence of fullerene molecules in these nanocluster associates.     

A Simulation Study of Due-date Assignment Rules in a Dynamic Job Shop

This paper is a report of a simulation study that investigates a dynamic approach to scheduling jobs in a multi-machine job shop. The workload information of a job is used in different forms to evaluate the shop performance based on three measures: mean job lateness, percentage of tardy jobs and lateness variance. Different combinations of due-date assignment methods and sequencing rules are compared based on specific performance criteria. The results indicate that using the cumulative distribution function of workload information can yield a better performance than using a proportional function of workload information or ignoring shop congestion information. A few situations are identified in which workload information is not critical.     

Towards an Operational Model for Prevention and Treatment of Asthma Attacks

Asthma is one of the major chronic diseases in many countries. At present there is no cure for asthma, but medical advances can help to reduce the chances of attacks of the condition. Efficient care for asthma involves complexity, uncertainty, variability and the use of scarce resources, and these are the same conditions that indicate a possible use for the modelling approach of operational research. This paper is concerned with a pilot model that was developed through joint work by medical professionals and operational researchers. The development of the model is explained and illustrative results indicate the potential value of the modelling approach for the care of asthma in the community.     

A Note on an Input Control Model of a Predictive Regression Interval

A well-known problem of prediction in linear regression models is to find a confidence interval for the random value of the dependent variable when the values of the independent variables are given. Such a situation may arise in economic quality control models when the independent variables are costly inputs and the dependent variable is some measure of quality or production. In such a circumstance, an important control objective may be to find values for the inputs that will maximize the lower limit of the prediction confidence interval for a fixed budget, or alternatively, to minimize the cost of the inputs for a fixed lower limit of the confidence interval. In this paper, we shall show that global optima can be found using known algorithms. The special case of simple linear regression is discussed and an illustrative example is provided.     

Solving a multi-objective simulation model using a hybrid response surface method and lexicographical goal programming approach—a case study on integrated circuit ink-marking machines

In an integrated circuit (IC) packaging plant, the ink-marking machine has a significantly higher throughput than the other processing machines. When periodic demand surges result in backlog orders or in lost customers, there is a need to increase system throughput. To resolve this problem, the purchase of a new machine often results in excess capacity in addition to added operation and acquisition costs. Therefore, the productivity improvement effort has priority over the machine purchase decision. This paper seeks to optimize both throughput and cycle time performance for IC ink-marking machines. While throughput increase is the primary objective, there is an acceptable cycle time limit for a feasible solution. It is a multi-objective problem. The proposed solution methodology constructed a simulation metamodel for the ink-marking operation by using a fractional factorial experimental design and regression analysis. It is then solved by a hybrid response surface method and lexicographical goal programming approach. Solution results illustrated a successful application.