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Operation Research, an approach to decision making based on the scientific method, makes extensive use of quantitative approaches to decision making. In addition to operation research, two other widely known and accepted names are management sciences and decision science interchangeably. The scientific management revolution of the early 1900s, initiated by Frederic W. Taylor, provided the foundation for the use of quantitative methods in management. But modern management science research is generally considered to have originated during the World War II period, when teams were formed to deal with strategic and tactical problems faced by the military. These teams, which often consisted of people with diverse specialities (e.g., mathematicians, engineers and behavioural scientists) were jointed together to solve a common problem through the utilization of the scientific method. After the war, many of these team members continued their research in the field of management science.

Operation Research is the scientific approach to managerial decision making. This approach starts with data. These data are processed into information that is valuable to people making decisions. This processing and manipulating of raw data into meaningful information is the heart of the Operation Research. Computers have been instrumental in the increasing use of Operation Research. Operation Research has been applied successfully to an increasingly wide variety of complex problems in business, government, health care, education and many other areas. The successful use of quantitative techniques usually results in a solution that is timely, accurate, flexible, economical, reliable and easy to understand and use. Today, operations research plays important roles in a variety of industries such as: airline - scheduling planes and crews, pricing tickets, taking reservations, and planning the size of the fleet, pharmaceutical - R& D management,

logistics companies - routing and planning,
financial services - credit scoring, marketing, and internal operations, lumber and wood products - managing forests and cutting timber, local government - deployment of emergency services, and

policy studies and regulation - environmental pollution, air traffic safety, AIDS, and criminal justice policy. As the field evolved, the core moved away from interdisciplinary teams to a focus on the development of mathematical models that can be used to model, improve, and even optimize real-world systems. These mathematical models include both deterministic models such as mathematical programming, routing or network flows and probabilistic models such as queuing, simulation and decision trees.

As indicated in the previous section, operation research encompasses a logical, systematic approach to problem solving, which closely parallels what is known as the scientific method for attacking problems. This approach, as shown in Figure 1, follows a generally recognized and ordered series of steps: (1) observation, (2) definition of problem, (3) model construction, (4) model solution and (5) implementation of solution results.

Figure 1: The steps in problem solving
The first step in operation research process is the identification of a problem that exists in the system (organization). The system must be continuously and closely observed so that problems can be identified as soon as they occur or are anticipated. Problems are not always the result of a crisis that must be reacted to but, instead, frequently involve a preventive or planning situation.

Definition of the Problem
Once it has been determined that a problem exists, the problem must be clearly and concisely defined. The limits of the problem and the degree to which it pervades other units of the organization must be included in the...
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