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The aim of this paper is to provide background information on the existing literature on experimental design techniques which may be applicable to the design of computer simulation experiments for industrial systems. Although major emphasis is placed on analysis of variance techniques, three other techniques of data analysis are considered—multiple ranking procedures, sequential sampling and spectral analysis. The paper treats four specific experimental design problems and several techniques for solving them. The four experimental design problems are: (1) the problem of stochastic convergence, (2) the problem of factor selection, (3) the problem of motive and (4) the many response problem. [ABSTRACT FROM AUTHOR]

The development of new large scale time-sharing systems has raised a number of problems for computation center management. Not only is it necessary to develop an appropriate hardware configuration for these systems, but appropriate software adjustments must be made. Unfortunately, these systems often do not respond to changes in the manner that intuition would suggest, and there are few guides to assist in the analysis of performance characteristics. The development of a comprehensive simulation model to assist in the investigation of these questions is described in this paper. The resulting model has a general purpose design and can be used to study a variety of timesharing systems. It can also be used to assist in the design and development of new time-sharing algorithms or techniques. For the sake of efficiency and greater applicability, the model was implemented in a limited FORTRAN subset that is compatible with most FORTRAN IV compilers. The use of the simulation is demonstrated by a study of the IBM 360/67 time-sharing system. [ABSTRACT FROM AUTHOR]