The Origin of Operations Research

Article

Vol. 17 // 2021

World war 2 switchboard featuring switchboard, old, and pbx concept copyright Piranhi via Creative Marke

I had completed a Master’s degree in Pure Mathematics before I made my way to the University of Texas at Austin to pursue a graduate degree in Operations Research (OR). It was not a common discipline to pursue and I found my way into the field via various mentors who encouraged me and helped me realize that I was well suited to the field.

And so began my journey into OR! I had the good fortune of finding some very interesting friends and colleagues at my program at UT. What struck me the most about our group was the various backgrounds we came from. Pure mathematics, engineering, statistics, business, military officers from different countries, and computer scientists. Together we made up the diverse OR group at UT Austin.

I loved all aspects of the program, especially the relationship Operations Research had with mathematics. As is the case with a lot of scientific fields, OR was born in battle and has quite an interesting history.

The field of Operations Research (OR) originated in the late 1930s during the Second World War when mathematicians and scientists employed it to aid the war effort. After the war ended applications for OR began to expand and it was soon applied to various disciplines such as engineering, economics, psychology, statistics, industrials, and government. Since it is a fusion of so many different fields, it is hard to define OR precisely. According to Miriam Webster, Operations Research is defined as “the application of scientific and especially mathematical methods to the study and analysis of problems involving complex systems”.

But OR is perhaps best understood by focusing on what it can do. Fundamentally, the field seeks to establish a rational basis for effective decision-making. In some sense, it is the science of optimizing decisions. Leveraging advancements in processing, large scale data analysis, and complex machine learning models, Operation Research promises better and better solutions to complex problems.

Today, you’ll find OR being used everywhere; from water resource engineering, financial modeling, military research and scheduling to resource management in various verticals.

The Birth of Operations Research

OR was born amidst the British Royal Air Force’s quest to use radar technology to ensure the defense of their homeland during WW-II. In order to utilize radar effectively, the RAF needed to not only detect enemy aircraft but also control the interception of these intruding aircraft. The challenge was taken up by a multidisciplinary group of researchers who left lab settings and participated in field operations, experimentation, and testing. The methods they developed were then quickly adopted by British armed forces to solve operational and technical problems. Thus, the field of OR laid its foundation on this collaboration across various disciplines.

It would not be an exaggeration to say that OR-based solutions helped the Allies win the war. U.S military services recognized the contributions and developments of OR and continued their support for the field, extending applications to combat modeling, logistics, and force planning. From these military origins, OR solutions were extended to address the operational and management problems of non-military organizations. And so operations research made its way into other verticals.

The OR Timeline

1936: Early in 1936, the British Air Ministry established a research station named “Bawdsey Research Station” near Felixstowe, Suffolk. The center was dedicated to pre-war radar experiments for both the Army and Air Force. A range of 100 miles was recorded for the radar in a reliable state after extensive trials and testing. In the same year, the Royal Air Force (RAF) Fighter Command was created. It was clear that radar technology would create new challenges and problems in fighter control. Therefore, in late 1936, some experiments were performed at Biggin Hill in Kent to make effective use of radar data for the purpose of fighter interception.

1937: In the summer of 1937, the first of three pre-war air defense exercises were carried out at the Bawdsey Research Station. Data from radar was fed into the warning and control system of air defense. For early experimentation, the exercise yielded very good results but some challenges such as filtration, transmission, and information tracking from radar were highlighted.

1938: A second air-defense exercise was conducted in July 1938. In this experiment, four radars were installed along the coast with the goal of obtaining aircraft locations. The control system showed promise, but results were mixed. The radar stations were transmitting conflicting information and it became clear that a new approach was needed to resolve these issues. On the same day, the first OR research team was selected and assigned to address this problem.

1939: A huge pre-war air-defense experiment was conducted which involved 110 anti-aircraft guns, 1300 aircraft, 33,000 men, 100 barrage balloons, and 700 searchlights. This exercise showed a great improvement in the air defense warning and control system, in part, due to the success of the OR team working on the problem.

1941: An Operational Research Section (ORS) was formed for the adoption of popular OR work in World War II. It was the responsibility of Coastal Command to extend the scope of OR and ensure long-range flights of aircraft with the capability to sight and attack the German U-boats. For this, a team of scientists was established who studied the tactical and strategic problems involved. The ultimate purpose was to employ quantitative techniques to make the most effective use of limited military resources.

1951: In 1951, the very first book on “Methods of Operations Research” was published by Morse and Kimball. The National Research Council of the USA formed a committee on Operations Research.

1952: The Operation Research Society of America was established.

Sources:
https://fas.org/sgp/crs/natsec/R45178.pdf
https://stars.library.ucf.edu/cgi/viewcontent.cgi?referer=https://www.google.com/&httpsredir=1&article=6054&context=rtd
http://lnmuacin.in/studentnotice/2020/operations%20Research.pdf
https://www.eolss.net/sample-chapters/C02/E6-132-31.pdf
https://www.atlantis-press.com/article/55912662.pdf
http://stars.library.ucf.edu/cgi/viewcontent.cgi?article=6054&context=rtd

The Evolution of Operations Research

Developments in Operations Research in the Military

1. Fast and Effective Decision Making

Today, the military employs cognitive ability, fast detection and analysis methods combined with empirical intuition to make faster and more effective decisions in daily operations. Artificial Intelligence and machine learning models process visual information, make decision trees, calculate probabilities, and perform reasoning in a matter of seconds to assist military officers.

2. Advanced Weapon Systems and Simulation Engines

Combat simulation engines are developed based on Big Data and AI. Through virtual reality technology and analytics, military exercises are streamlined. Using this technology the performance and capability of advanced weapon systems are also enhanced.

3. Collaborative Decision-Making

Big Data is playing a vital role in accelerating decision-making in military operations. Military experts are making use of scientific decision-making instead of traditional decision-making processes that are based on personal experience.

4. Correlation Analysis using Big Data

Operations Research is updating methods of correlational analysis, applying these techniques to huge datasets of military operations, patterns, and rules of simultaneous event occurrence. Key attributes are filtered from massive data, and data mining techniques are used to extract patterns and explore operational rules.

Though OR was born in battle, it is now being widely used to solve problems across a variety of verticals. Effective decision making is a critical need in all fields. With enhanced computing capabilities, the rise of big data, and machine learning, we will be able to make even better decisions for the future.

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