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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]

Improvements to the exhaustive search method of best-match file searching have previously been achieved by doing a preprocessing step involving the calculation of distances from a reference point. This paper discusses the proper choice of reference points and extends the previous algorithm to use more than one reference point. It is shown that reference points should be located outside of data clusters. The results of computer simulations are presented which show that large improvements can be achieved by the proper choice and location of multiple reference points. [ABSTRACT FROM AUTHOR]

An algorithm is presented that searches for the location, "i," of the first occurrence of a character string, "pat," in another string, "string," During the search operation, the characters of pat are matched starting with the last character of pat. The information gained by starting the match at the end of the pattern often allows the algorithm to proceed in large jumps through the text being searched. Thus the algorithm has the unusual property that, in most cases, not all of the first i characters of string are inspected. The number of characters actually Inspected (on the average) decreases as a function of the length of pat. For a random English pattern of length 5, the algorithm will typically inspect i/4 characters of string before finding a match at i. Furthermore, the algorithm has been implemented so that (on the avenge) fewer than i + patlen machine instructions are executed. These conclusions are supported with empirical evidence and a theoretical analysis of the average behavior of the algorithm. The worst case behavior of the algorithm is linear in i + patlen, assuming the availability of array space for tables linear in pollen plus the size of the alphabet. [ABSTRACT FROM AUTHOR]

Four different sequential sampling procedures are applied to the analysis of data generated by a computer simulation experiment with a multi-item inventory model. For each procedure the cost of computer time required to achieve given levels of statistical precision is calculated. Also the cost of computer time using comparable fixed sample size methods is calculated. The computer costs of fixed sample size procedures versus sequential sampling procedures are compared. [ABSTRACT FROM AUTHOR]