What is Operations Research?

Operations Research (O.R.), or operational research in the U.K, is a discipline that deals with the application of advanced analytical methods to help make better decisions. The terms management science and analytics are sometimes used as synonyms for operations research. Employing techniques from other mathematical sciences, such as mathematical modeling, statistical analysis, and mathematical optimization, operations research arrives at optimal or near-optimal solutions to complex decision-making problems. Operations research overlaps with other disciplines, notably industrial engineering and operations management. It is often concerned with determining a maximum (such as profit, performance, or yield) or minimum (such as loss, risk, or cost.) Operations research encompasses a wide range of problem-solving techniques and methods applied in the pursuit of improved decision-making and efficiency, such as simulation, mathematical optimization, queuing theory, Markov decision processes, economic methods, data analysis, statistics, neural networks, expert systems, and decision analysis. 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, O.R. also has strong ties to computer science. Operations 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. The major sub-disciplines in modern operations research, as identified by the INFORMS journal Operations Research, are:

  • Computing and information technologies
  • Environment, energy, and natural resources
  • Financial Engineering
  • Manufacturing, service science, and supply chain management
  • Marketing Science
  • Policy modeling and public sector work
  • Revenue management
  • Simulation
  • Stochastic models
  • Transportation

What is Management Science?

Management science (MS), is an interdisciplinary branch of applied mathematics, engineering and sciences that uses various scientific research-based principles, strategies, and analytical methods including mathematical modeling, statistics and algorithms to improve an organization's ability to enact rational and meaningful management decisions. The discipline is typically concerned with maximizing profit, assembly line performance, crop yield, bandwidth, etc or minimizing expenses, loss, risk, etc.

Management science is concerned with a number of different areas of study including developing and applying models and concepts that may prove useful in helping to illuminate management issues and solve problems. Management science research can be done on three levels:

  • A fundamental level that lies in three mathematical disciplines: probability, optimization, and dynamic systems theory,
  • A modeling level that builds models, gathers data, and analyzes them mathematically, and
  • An application level, just as any other engineering discipline that has strong aspirations to make a practical impact in the real world.


Applications of management science are abundant in industry such as airlines, manufacturing companies, service organizations, military branches, and in government. The range of problems and issues to which management science has contributed insights and solutions is vast. It includes:

  • scheduling airlines, both planes and crew,
  • deciding the appropriate place to place new facilities such as a warehouse or factory,
  • managing the flow of water from reservoirs,
  • identifying possible future development paths for parts of the telecommunications industry,
  • establishing the information needs and appropriate systems to supply them within the health service, and
  • identifying and understanding the strategies adopted by companies for their information systems.

Thanks to INFORMS site

Usefull materials

About Operations Reserach topic, I report two links from the site of prof. Giovanni Righini (Università degli Studi di Milano):