2.2 Historical Development : Management science is also referred to by other names such as quantitative analysis,
decision sciences, systems analysis etc. Even though the application of scientific methods to
management problems is comparatively more recent, some of the underlying principles were
developed many centuries ago. For example, the probability theory was developed by Pascal and
Calculus by Newton sometime in the 17
th
century. The dawn of the 20
th
century saw some early
developments in the area of inventory control by Ford Harris and R.H. Wilson, some dynamic
models developed by Markov and an analysis of queuing theory by A.K. Erlang. However,
management science as a field of study began during world war II in Britain by a group of scientists
under professor P.M.S. Blackelt. Commissioned by the army to analyse and solve some complex
army operational decision problems. The group was known as army operational research group
that was involved in finding solutions to highly complex and strategic situations such as convoy
routing searching of submarines, optimum depth for detonating anti submarine charges, selecting
optimum gun sites, planning defense tactics against suicides attacks etc. This was the birth of the
operations research fields, which has since been successfully applied in solving problems in a
variety of areas including resource allocation where the resources are scarce and exhaustible,
inventory, control problems, maintenance and replacement, game theory, waiting line problems,
routing etc.
Following the war, the applications of operations research techniques extended into industry
specially large size industries such as oil refineries, steel and paper mills. The decades of 1950’s
and 1960’s saw a dramatic development and refinement of these solutions to many complex
industrial, business and military problems and these solutions were further aided by the development
and extensive use of fast computers which handled large quantities of data and calculated various
relationships of a large number of variables in a short period of time.