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 the “Student's t-distribution", which otherwise would have been known as Gosset's t-distribution". This historical milestone opened the doors for the application of simulation in the field of industrial control processes as well as to synergies generated by simulation based on experimentation and analysis techniques, to discover exact solutions to typical industry and engineering problems. 3 THE SIMULATION FORMATIVE PERIOD (1945–1970)
In the mid-1940s two major developments set the stage for the rapid evolution of the field of simulation: * The construction of the first computers used for specific purposes, such as the ENIAC (Electronic Numerical Integrator and Computer). * The work of Stanislaw Ulam, John Von Neumann and other scientists to use the Montecarlo method in modern computers, solving neutron diffusion problems in the design and development of the hydrogen bomb. Ulam and Von Neumann were present on the Manhattan project.
Ulam’s fondness for card games and his attempts to find a easier way to estimate the probabilities of certain events in those card games apparently led him to the idea that a “Monte Carlo” approach to the problems of mathematical physics might be effective. The increasing availability of general-purpose electronic computers in the 1950s set the stage for the rapid proliferation of simulation techniques and applications in other disciplines.
In 1960, Keith Douglas Tocher, a professor of operational research at the University of Southampton, developed the General Simulation Program (GSP), the first general-purpose simulator, as a tool for systematically building a simulation of an industrial plant that comprises a set of machines which ran in the following cycles: In use, On Standby, Not available and Fault. Thus, the simulations of status changes would define the definite status of the plant production. This work also led to the first book on simulation: The Art of...