Operations research

Operations research (British English: operational research) (U.S. Air Force Specialty Code: Operations Analysis), often shortened to the initialism OR, is a discipline that deals with the development and application of analytical methods to improve decision-making.^[1] The term management science is occasionally used as a synonym.^[2]

For the academic journal, see Operations Research (journal).

Employing techniques from other mathematical sciences, such as modeling, statistics, and optimization, operations research arrives at optimal or near-optimal solutions to decision-making problems. Because of its emphasis on practical applications, operations research has overlapped with many other disciplines, notably industrial engineering. Operations research is often concerned with determining the extreme values of some real-world objective: the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost). Originating in military efforts before World War II, its techniques have grown to concern problems in a variety of industries.^[3]

Computing and information technologies

Financial engineering

service sciences, and supply chain management

Manufacturing

Policy modeling and public sector work

Revenue management

Simulation

Stochastic models

Transportation theory (mathematics)

for strategies

Game theory

Linear programming

Nonlinear programming

in NP-complete problem specially for 0-1 integer linear programming for binary

Integer programming

in Aerospace engineering and Economics

Dynamic programming

used in Cryptography, Quantum computing

Information theory

for solutions of Quadratic equation and Quadratic function

Quadratic programming

Operational research (OR) encompasses the development and the use of a wide range of problem-solving techniques and methods applied in the pursuit of improved decision-making and efficiency, such as simulation, mathematical optimization, queueing theory and other stochastic-process models, Markov decision processes, econometric methods, data envelopment analysis, ordinal priority approach, neural networks, expert systems, decision analysis, and the analytic hierarchy process.^[4] Nearly all of these techniques involve the construction of mathematical models that attempt to describe the system. Because of the computational and statistical nature of most of these fields, OR also has strong ties to computer science and analytics. Operational researchers faced with a new problem must determine which of these techniques are most appropriate given the nature of the system, the goals for improvement, and constraints on time and computing power, or develop a new technique specific to the problem at hand (and, afterwards, to that type of problem).

The major sub-disciplines (but not limited to) in modern operational research, as identified by the journal Operations Research^[5] and The Journal of the Operational Research Society ^[6] are:

or project planning: identifying those processes in a multiple-dependency project which affect the overall duration of the project

Critical path analysis

: designing the layout of equipment in a factory or components on a computer chip to reduce manufacturing time (therefore reducing cost)

Floorplanning

: for instance, setup of telecommunications or power system networks to maintain quality of service during outages

Network optimization

problems

Resource allocation

Facility location

Assignment problem

: looking for a target

Bayesian search theory

Optimal search

such as determining the routes of buses so that as few buses are needed as possible

Routing

: managing the flow of raw materials and products based on uncertain demand for the finished products

Supply chain management

Project production activities: managing the flow of work activities in a capital project in response to system variability through operations research tools for variability reduction and buffer allocation using a combination of allocation of capacity, inventory and time^[33]

[32]

Efficient messaging and customer response tactics

: automating or integrating robotic systems in human-driven operations processes

Automation

: globalizing operations processes in order to take advantage of cheaper materials, labor, land or other productivity inputs

Globalization

Transportation: managing transportation and delivery systems (Examples: LTL shipping, intermodal freight transport, travelling salesman problem, driver scheduling problem)

freight

Scheduling

Personnel staffing

Blending of raw materials in oil refineries

Determining optimal prices, in many retail and B2B settings, within the disciplines of

pricing science

: Cutting small items out of bigger ones.

Cutting stock problem

Finding the optimal parameter (weights) setting of an algorithm that generates the realisation of a in Baroque compositions (classical music) by using weighted local cost and transition cost rules

figured bass

Operational research is also used extensively in government where evidence-based policy is used.

Scheduling (of airlines, trains, buses etc.)

Assignment (assigning crew to flights, trains or buses; employees to projects; commitment and dispatch of power generation facilities)

Facility location (deciding most appropriate location for new facilities such as warehouses; factories or fire station)

Hydraulics & Piping Engineering (managing flow of water from reservoirs)

Health Services (information and supply chain management)

Game Theory (identifying, understanding; developing strategies adopted by companies)

Urban Design

Computer Network Engineering (packet routing; timing; analysis)

Telecom & Data Communication Engineering (packet routing; timing; analysis)

Societies and journals[edit]

Societies[edit]

The International Federation of Operational Research Societies (IFORS)^[39] is an umbrella organization for operational research societies worldwide, representing approximately 50 national societies including those in the US,^[40] UK,^[41] France,^[42] Germany, Italy,^[43] Canada,^[44] Australia,^[45] New Zealand,^[46] Philippines,^[47] India,^[48] Japan and South Africa.^[49] For the institutionalization of Operations Research, the foundation of the (IFORS) in 1960 was of decisive importance, which stimulated the foundation of national OR societies in Austria, Switzerland and Germany. IFORS held important international conferences every three years since 1957.^[50] The constituent members of IFORS form regional groups, such as that in Europe, the Association of European Operational Research Societies (EURO).^[51] Other important operational research organizations are Simulation Interoperability Standards Organization (SISO)^[52] and Interservice/Industry Training, Simulation and Education Conference (I/ITSEC)^[53]

In 2004, the US-based organization INFORMS began an initiative to market the OR profession better, including a website entitled The Science of Better^[54] which provides an introduction to OR and examples of successful applications of OR to industrial problems. This initiative has been adopted by the Operational Research Society in the UK, including a website entitled Learn About OR.^[55]

Journals of INFORMS[edit]

The Institute for Operations Research and the Management Sciences (INFORMS) publishes thirteen scholarly journals about operations research, including the top two journals in their class, according to 2005 Journal Citation Reports.^[56] They are:

R. E. Bellman, Dynamic Programming, Princeton University Press, Princeton, 1957

Abraham Charnes, William W. Cooper, Management Models and Industrial Applications of Linear Programming, Volumes I and II, New York, John Wiley & Sons, 1961

Abraham Charnes, William W. Cooper, A. Henderson, An Introduction to Linear Programming, New York, John Wiley & Sons, 1953

C. West Churchman, Russell L. Ackoff & E. L. Arnoff, Introduction to Operations Research, New York: J. Wiley and Sons, 1957

George B. Dantzig, Linear Programming and Extensions, Princeton, Princeton University Press, 1963

Lester K. Ford, Jr., D. Ray Fulkerson, Flows in Networks, Princeton, Princeton University Press, 1962

Jay W. Forrester, Industrial Dynamics, Cambridge, MIT Press, 1961

L. V. Kantorovich, "Mathematical Methods of Organizing and Planning Production" Management Science, 4, 1960, 266–422

Ralph Keeney, Howard Raiffa, Decisions with Multiple Objectives: Preferences and Value Tradeoffs, New York, John Wiley & Sons, 1976

H. W. Kuhn, "The Hungarian Method for the Assignment Problem," Naval Research Logistics Quarterly, 1–2, 1955, 83–97

H. W. Kuhn, A. W. Tucker, "Nonlinear Programming," pp. 481–492 in Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability

B. O. Koopman, Search and Screening: General Principles and Historical Applications, New York, Pergamon Press, 1980

Tjalling C. Koopmans, editor, Activity Analysis of Production and Allocation, New York, John Wiley & Sons, 1951

Charles C. Holt, Franco Modigliani, John F. Muth, Herbert A. Simon, Planning Production, Inventories, and Work Force, Englewood Cliffs, NJ, Prentice-Hall, 1960

Philip M. Morse, George E. Kimball, Methods of Operations Research, New York, MIT Press and John Wiley & Sons, 1951

Robert O. Schlaifer, Howard Raiffa, Applied Statistical Decision Theory, Cambridge, Division of Research, Harvard Business School, 1961