Operations research

1. Operations research provides analytical methods of finding solutions to problems involving the operations of a system, so as to provide those in control of the system with optimum solutions to the problems. From a large number of feasible combinations, the optimum combination is identified for achieving the given objective under certain constraints. The major phase of an OR project are: formulation of the problem; constructing a mathematical model to represent the system under study; deriving a solution from the model; testing the model and the solution derived from it; establishing controls over the solution; putting the solution to work (implementation).

2. OR provides solutions for many production-oriented problems, particularly those related to: inventory processes and control (using: economic-order-quantity equations, and linear, dynamic, and quadratic programming); resource allocation processes (using: linear and other types of mathematical programming); waiting-time processes (using: queuing theory, sequencing theory, line-balancing theory); replacement processes; competitive processes (using: theory of games); and combined processes.

3. The basis for problem solution is a mathematical model or representation of selected aspects of the real world system in question. The model is manipulated according to rules of logic, and the consequences of policy decisions are predicted from model solutions. The objective of manipulating the model is usually to determine an optimum solution without having to manipulate the real world system, thus providing guidance for the solution of the real world problem.

4. The earlier distinction between operations research, scientific management and management science is no longer considered meaningful. A distinction is however made between OR and systems analysis. OR tends to accept specified objectives and given assumptions about the circumstances, the hardware, etc., and then attempts to compute an optimum solution. The epistemology of OR is that of the exact sciences, assuming that the empirical data are accurate enough to make refined calculations worthwhile. On the other hand, the epistemology of systems analysis is that of the inexact sciences. Statistics may be used and emphasis is placed on techniques for dealing with uncertainty, such as sensitivity tests, the use of ranges, alternative scenarios, etc. In effect, OR is oriented toward problems in which the element of calculation is dominant, and therefore, in which mathematics can be thought of as a substitute for rather than as an aid to, judgement. Both are scientific approaches to problem solving, but systems analysis is more complex, and less neat and tidy, embodying a much larger percentage of nonquantitative elements which influence the outcome.