INTRODUCTION TO OPERATION RESEARCH
INTRODUCTION
Although it is a distinct discipline in its own
right, Operations Research (O.R.) has also become an integral part of the
Industrial Engineering (I.E.) profession.
This is hardly a matter of surprise when one considers that they both
share many of the same objectives, techniques and application areas. O.R. as a formal subject is about fifty years
old and its origins may be traced to the latter half of World War II. Most of the O.R. techniques that are commonly
used today were developed over (approximately) the first twenty years following
its inception. During the next thirty or
so years the pace of development of fundamentally new O.R. methodologies has
slowed somewhat. However, there has been
a rapid expansion in (1) the breadth of problem areas to which O.R. has been
applied, and (2) in the magnitudes of the problems that can be addressed using
O.R. methodologies. Today, operations
research is a mature, well-developed field with a sophisticated array of
techniques that are used routinely to solve problems in a wide range of
application areas
This
chapter will provide an overview of O.R. from the perspective of an Industrial
Engineer. A brief review of its
historical origins is first provided.
This is followed by a detailed discussion of the basic philosophy behind
O.R. and the so-called “O.R. approach.”
The chapter concludes with several examples of successful applications
to typical problems that might be faced by an Industrial Engineer. Broadly speaking, an O.R. project comprises
three steps: (1) building a model, (2) solving it, and (3) implementing the
results. The emphasis of this chapter is
on the first and third steps. The second
step typically involves specific methodologies or techniques, which could be
quite sophisticated and require significant mathematical development. Several important methods are overviewed
elsewhere in this handbook. The reader
who has an interest in learning more about these topics is referred to one of
the many excellent texts on O.R. that are available today and that are listed
under "Further Reading" at the end of this chapter, e.g., Hillier and
Lieberman (1995), Taha (1997) or Winston (1994).
A
HISTORICAL PERSPECTIVE
While there is no clear date that marks the
birth of O.R., it is generally accepted that the field originated in England
during World War II. The impetus for its
origin was the development of radar defense systems for the Royal Air Force, and
the first recorded use of the term Operations Research is attributed to a
British Air Ministry official named A. P. Rowe who constituted teams to do
“operational researches” on the communication system and the control room at a
British radar station. The studies had
to do with improving the operational efficiency of systems (an objective which
is still one of the cornerstones of modern O.R.). This new approach of picking an “operational”
system and conducting “research” on how to make it run more efficiently soon
started to expand into other arenas of the war.
Perhaps the most famous of the groups involved in this effort was the
one led by a physicist named P. M. S. Blackett which included physiologists,
mathematicians, astrophysicists, and even a surveyor. This multifunctional team focus of an
operations research project group is one that has carried forward to this
day. Blackett’s biggest contribution was
in convincing the authorities of the need for a scientific approach to manage
complex operations, and indeed he is regarded in many circles as the original
operations research analyst.
O.R. made its way to the United States a few
years after it originated in England.
Its first presence in the U.S. was through the U.S. Navy’s Mine Warfare
Operations Research Group; this eventually expanded into the Antisubmarine
Warfare Operations Research Group that was led by Phillip Morse, which later
became known simply as the Operations Research Group. Like Blackett in Britain, Morse is widely
regarded as the “father” of O.R. in the United States, and many of the
distinguished scientists and mathematicians that he led went on after the end
of the war to become the pioneers of O.R. in the United States.
In the years immediately following the end of
World War II, O.R. grew rapidly as many scientists realized that the principles
that they had applied to solve problems for the military were equally
applicable to many problems in the civilian sector. These ranged from short-term problems such as
scheduling and inventory control to long-term problems such as strategic
planning and resource allocation. George
Dantzig, who in 1947 developed the simplex algorithm for Linear Programming
(LP), provided the single most important impetus for this growth. To this day, LP remains one of the most
widely used of all O.R. techniques and despite the relatively recent
development of interior point methods as an alternative approach, the simplex
algorithm (with numerous computational refinements) continues to be widely
used. The second major impetus for the
growth of O.R. was the rapid development of digital computers over the next
three decades. The simplex method was
implemented on a computer for the first time in 1950, and by 1960 such
implementations could solve problems with about 1000 constraints. Today, implementations on powerful
workstations can routinely solve problems with hundreds of thousands of
variables and constraints. Moreover, the
large volumes of data required for such problems can be stored and manipulated
very efficiently.
Once the simplex method had been invented and
used, the development of other methods followed at a rapid pace. The next
twenty years witnessed the development of most of the O.R. techniques that are
in use today including nonlinear, integer and dynamic programming, computer
simulation, PERT/CPM, queuing theory, inventory models, game theory, and
sequencing and scheduling algorithms.
The scientists who developed these methods came from many fields, most
notably mathematics, engineering and economics.
It is interesting that the theoretical bases for many of these
techniques had been known for years, e.g., the EOQ formula used with many
inventory models was developed in 1915 by Harris, and many of the queuing
formulae were developed by Erlang in 1917.
However, the period from 1950 to 1970 was when these were formally
unified into what is considered the standard toolkit for an operations research
analyst and successfully applied to problems of industrial significance. The following section describes the approach
taken by operations research in order to solve problems and explores how all of
these methodologies fit into the O.R. framework
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