History of Simulation
1. INTRODUCTION
Simulation history is viewed in different angles including:
-simulation uses e.g. analysis, training, research.
- types of simulation models e.g. discrete-event, continuous, combined discrete
- simulation programming languages or environments e.g. Arena, SIMSCRIPT,SLAM and - application domains or communities of interest e.g. communications, manufacturing, military, transportation).
The objective of this history is to highlight people, places, and events that have marked the development of discrete-event and Monte Carlo simulation.
2. THE PRE-COMPUTER ERA: (1777–1945)
Monte Carlo simulation method is generally considered to have originated with a “needle experiment” in 1777 by one Claudio Rocchini Buffon. The experiment is to “throw” needles onto a plane with equally spaced parallel lines in order to estimate the value of π.
This mathematical model is based on a needle of a certain length dropped onto a plane ruled with parallel lines separated by units. What is the probability of the needle crossing a line?
In 1812 Laplace improved and corrected the Buffon solution and since then it is known as the Buffon-Laplace solution. Later on, the statistician William Sealy Gosset, who worked at the Arthur Guinness Brewery, had already begun to apply statistical knowledge in the brewery and on his own farming estate. The special interest of Gosset in barley crops led him to speculate that experiments should not only be designed with a view to improving average production levels, but they should also aim at developing stronger strains of barley, which were not affected by variations in soil and climate.
To avoid future leaks of confidential information, Guinness forbade his employees to publish any type of article regardless of its content, hence the use that Gosset made in his publications of the pseudonym “Student”, to prevent his employer from discovering his true identity. That is why his most famous achievement is known as
Simulation history is viewed in different angles including:
-simulation uses e.g. analysis, training, research.
- types of simulation models e.g. discrete-event, continuous, combined discrete
- simulation programming languages or environments e.g. Arena, SIMSCRIPT,SLAM and - application domains or communities of interest e.g. communications, manufacturing, military, transportation).
The objective of this history is to highlight people, places, and events that have marked the development of discrete-event and Monte Carlo simulation.
2. THE PRE-COMPUTER ERA: (1777–1945)
Monte Carlo simulation method is generally considered to have originated with a “needle experiment” in 1777 by one Claudio Rocchini Buffon. The experiment is to “throw” needles onto a plane with equally spaced parallel lines in order to estimate the value of π.
This mathematical model is based on a needle of a certain length dropped onto a plane ruled with parallel lines separated by units. What is the probability of the needle crossing a line?
In 1812 Laplace improved and corrected the Buffon solution and since then it is known as the Buffon-Laplace solution. Later on, the statistician William Sealy Gosset, who worked at the Arthur Guinness Brewery, had already begun to apply statistical knowledge in the brewery and on his own farming estate. The special interest of Gosset in barley crops led him to speculate that experiments should not only be designed with a view to improving average production levels, but they should also aim at developing stronger strains of barley, which were not affected by variations in soil and climate.
To avoid future leaks of confidential information, Guinness forbade his employees to publish any type of article regardless of its content, hence the use that Gosset made in his publications of the pseudonym “Student”, to prevent his employer from discovering his true identity. That is why his most famous achievement is known as
References: Burks, A. W., and A. R. Burks. 1981. The ENIAC: First general-purpose electronic computer. IEEE Annals of the History of Computing 3 (4): 310–399. Conway, R. W., B. M. Johnson, and W. L. Maxwell. 1959. Some problems of digital systems simulation. Management Science 6 (1): 92–110.Conway, R. W. 1963. Some tactical problems in digital simulation. Management Science 10 (1): 47–61.Cooper, N. C., ed. 1988. From cardinals to chaos: Reflections on the life and legacy of Stanislaw Ulam. Cambridge: Cambridge University Press. Gordon, G. 1981. The development of the General Purpose Simulation System. In History of programming languages, ed. R. L. Wexelblatt, 403–437. New York: Academic Press.