Abstract

Operational Research (OR) is the discipline that applies analytical methods, most of which are mathematical, statistical and computational in nature, to arrive at optimal or near-optimal solutions to complex decision-making problems. OR has strong ties with disciplines such as Mathematics, Business and Management, Industrial Engineering and Computer Science. The growth of the OR field has meant greater specialization and division into subfields (Miser, 2000) which sometime lack distinct boundaries. A topical example here is the emerging research area of Big Data, Business Intelligence and Analytics. They enable introspection of large corpus of data and provide both data-driven and predictive insights for organizational decision-making; this again is a fertile area of enquiry for OR research, as also for Computer Science (e.g., technologies associated with Big Data storage and retrieval), Information Systems (e.g., business intelligence dashboards) and Mathematics and Statistics (e.g., algorithms for data mining, predictive analytics). The fuzzy boundaries of the discipline are further evidenced by the fact that the terms ‘OR’ and ‘MS’ (Management Science) have not been absorbed as one but both exist conjoint and make the well-known OR/MS discipline. The lack of boundaries is a reflection of the interdisciplinary nature of the discipline.

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