What are the main importance of operations research?
OPERATIONS RESEARCH
Operations research has been called the science and technology of decision making. The scientific component is concerned with the ideas and processes for expressing and modeling decision problems by determining the decision maker's objectives and the constraints under which he or she should, or should, operate. It is also related to mathematical methods, called algorithms, for optimizing numerical systems, using the resulting data to populate models. The technical component deals with the software and hardware tools to collect and communicate data, organize them, use them to build models, optimize these models, and report results.
Operations research models and methods have demonstrated their relevance in a wide range of applications. This broadness creates opportunities and challenges. A great opportunity is that many supply chain problems can be analyzed using optimization models and algorithms that are taken more or less "off-the-shelf" and adapted quickly for use. But the details of a given problem matter. Therefore, a major challenge in any specific situation is precisely defining an appropriate model. This book is devoted to the examination and expansion of these opportunities and challenges.
Operations research was one of the disciplines that came to life at the beginning of the information revolution in the mid-1940s. The revolution began with the need for numerical computing in military operations during World War II. Despite these very early applications, later developments in information technology in business were concerned with methods of data acquisition, communication, and management as opposed to numerical computation. These concerns persisted until very recently. Interest in numerical computation in business has now increased greatly, as has the widespread use of electronic spreadsheets and sophisticated graphics programs, as well as a renewed interest in operations research models.
Unfortunately, between 1970 and 1985, operations research moved away from its origins as companies were more concerned with the ways in which the data were obtained than the methods of analysis. During that period, information technology lagged behind theory to support the practical implementation of the operations research model. Often the data needed for a realistic model were not readily available, or could not be obtained in time. Without opportunities to work on real world problems. Academics and other researchers in the field kept busy by expanding the theory in directions with little practical relevance.
Despite the shortcomings of the past, the future of operations research is bright, especially for new and expanding applications. Increasing interest by managers in.
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