Curriculum 68: Recommendations for academic programs in computer science: a report of the ACM curriculum committee on computer science

Traffic flow theory : a monograph

The purpose of this paper is to present a comparison of some computer simulation languages and of some of the packages by which each is implemented. Some considerations involved in comparing software packages for digital computers are discussed in Part I. The issue is obvious: users of digital computers must choose from available languages or write their own. Substantial costs can occur, particularly in training, implementation and computer time if an inappropriate language is chosen. More and more computer simulation languages are being developed: comparisons and evaluations of existing languages are useful for designers and implementers as well as users.The second part is devoted to computer simulation and simulation languages. The computational characteristics of simulation are discussed with special attention being paid to a distinction between continuous and discrete change models. Part III presents a detailed comparison of six simulation languages and packages: SIMSCRIPT, CLP, CSL, GASP, GPSS and SOL. The characteristics of each are summarized in a series of tables. The implications of this analysis for designers of languages, for users, and for implementers are developed.The conclusion of the paper is that the packages now available for computer simulation offer features which none of the more general-purpose packages do and that analysis of strengths and weaknesses of each suggests ways in which both current and future simulation languages and packages can be improved.

Computer simulation—discussion of the technique and comparison of languages

In an excellent article from a recent issue of this journal, Sellar, Stoll and Chavas (1985) make a technical error which causes them to misstate their closed-ended estimates of willingness to pay. Truncation of the estimated cummulative distribution function must we made explicit in compution of willingness to pay.

Validation of empirical measures of welfare change: comment

Experimental design considerations have been virtually ignored by economists who have conducted computer simulation experiments with models of economic systems. The objective of this paper is to spell out in detail the relationship between existing experimental design techniques and techniques of data analysis and the design of simulation experiments with economic systems. We begin by defining the problem of experimental design as applied to computer simulation experiments. With the aid of an example model, we explore several techniques of data analysis and a number of specific experimental design problems. Although this paper is oriented towards the design of computer simulation experiments in economics, the techniques which are discussed are of a general nature and should be applicable to the design of simulation experiments in other disciplines.

https://www.jstor.org/stable/info/2283781

Computer Simulation Experiments with Economic Systems: The Problem of Experimental Design

Various methods for improving the efficiency of statisticals imulation of complex systems are described and illustratedf or simple queuing situations. The paper proposes that the efficiency and effectiveness of statistical simulations can be increased throught he adaptation of experimentadl esign principles which exploit any qualitative knowledge surrounding the problem understudy. Some techniques explored are: proportional sampling fixed sequence sampling importance sampling and the use of concomitant information.

S. Ben-Tuvia

Papers

The Efficiency of Statistical Simulation Procedures