Abstract
Operations research (OR) is both a profession and an academic discipline. It involves the application of advanced analytical methods to improve executive and management decisions. This survey highlights the types of OR models and techniques in common use. It explores the roots of OR and its theoretical and professional evolution, and presents the current trends which shape its future.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsBibliography
Arrow, K., S. Karlin, and H. Scarf. 1958. Studies in the mathematical theory of inventory and production. Stanford: Stanford University Press.
Bellman, R. 1957. Dynamic programming. Princeton: Princeton University Press.
Bixby, R. 2002. Solving real-world linear programs: a decade and more of progress. Operations Research 50: 3–15.
Bonder, S. 1979. Changing the future of operations research. Operations Research 27: 209–224.
Charnes, A., and W. Cooper. 1959. Chance-constrained programming. Management Science 6: 73–79.
Charnes, A., and Cooper, W. 1961. Management models and industrial applications of linear programming, vols. 1 and 2. New York: Wiley.
Churchman, C. 1979. Paradise regained: A hope for the future of systems design education. In Education in systems science, ed. B. Bayraktar. London: Taylor and Francis.
Churchman, C., R. Ackoff, and E. Arnoff. 1957. Introduction to operations research. New York: Wiley.
Cook, S. 1971. The complexity of theorem-proving procedures. Proceedings of the Association for Computing Machinery Annual Symposium on the Theory of Computing 3: 151–158.
Cornuéjols, G. 2003. The strong perfect graph theorem. Optima: The Mathematical Programming Society Newsletter 70 (June): 2–6.
Dando, M.R., and R. Sharp. 1978. Operational research in the UK in 1977: The cases and consequences of a myth? Journal of the Operational Research Society 29: 939–949.
Dantzig, G. 1963. Linear programming and extensions. Princeton: Princeton University Press.
Denizel, M., B. Usdiken, and D. Tuncalp. 2003. Drift or shift? Continuity, change, and international variation in knowledge. Operations Research 51: 711–720.
Fleischer, L. 2000. Recent progress in submodular function minimization. Optima: The Mathematical Programming Society Newsletter 64 (September): 1–11.
Ford, L. Jr., and D. Fulkerson. 1962. Flows in networks. Princeton: Princeton University Press.
Geoffrion, A. 1992. Forces, trends and opportunities in MS/OR. Operations Research 40: 423–445.
Gomory, R. 1958. Essentials of an algorithm for integer solutions to linear programs. Bulletin of the American Mathematical Society 64: 275–278.
House, A. 1952. The founding meeting of the society. Journal of the Operations Research Society of America 1: 18–32.
INFORMS (Institute for Operations Research and Management Science). About operations research. Online. Available at http://www.informs.org/index.php? c = 49&kat = + About + Operations + Research&p = 17|. Accessed 22 Aug 2006.
Kantorovich, L. 1939. Mathematical methods of organising and planning production. Leningrad University [in Russian]. Trans. R. Campbell and W. Marlow, Management Science 6(1960): 366–422.
Karmarkar, N. 1984. A new polynomial time algorithm for linear programming. Combinatorica 4: 373–395.
Karp, R. 1972. Reducibility among combinatorial problems. In Complexity of computer computations, ed. R. Miller and J. Thatcher. New York: Plenum Press.
Khachian, L. 1979. A polynomial algorithm in linear programming. Doklady Akademii Nauk SSSR 224: 1093–1096.
Khachian, L. 1980. Polynomial algorithms in linear programming. Zhurnal vychisditel’noi matematiki i matematicheskoi 20: 51–68.
Kuhn, H., and A. Tucker. 1951. Nonlinear programming. In Proceedings of the second Berkeley symposium on mathematical statistics and probability, ed. J. Neyman. Berkeley: University of California Press.
Lemke, C. 1954. The dual method of solving the linear programming problem. Naval Research Logistic Quarterly 1: 36–47.
Lemke, C. 1965. Bimatrix equilibrium points and mathematical programming. Management Science 11: 681–689.
Little, J. 1986. Research opportunities in the decision and management sciences. Management Science 32 (1): 1–13.
Miser, H. 1978. The history, nature and use of operations research. In Handbook of operations research, ed. J. Moder and S. Elmaghraby, vol. 1. New York: Van Nostrand Reinhold.
National Academy of Sciences. 1976. Systems analysis and operations research: A tool for policy and program planning for developing countries. Report of an ad hoc panel. Washington, DC: National Academy of Sciences.
Pocock, J. 1956. Operations research: A challenge to management. In Operations research. Special report no. 13. New York: American Management Association.
Quesnay, F. 1759. Tableau économique. In Paris, ed. M. Kuczynski and R. Meek, 3rd ed. London: Macmillan. 1972.
Raiffa, H. 1968. Decision analysis: Introductory lectures on choices and uncertainty. New York: Addison-Wesley.
Roundy, R. 1985. Effective integer ratio lot-sizing for one warehouse multi-retailer systems. Management Science 31: 1416–1430.
Roundy, R. 1986. Effective lot-sizing rule for a multi-product multi stage production/inventory system. Mathematics of Operations Research 11: 699–727.
The OR Society. What operational research is. Online. Available at http://www.orsoc. org.uk/orshop/(aamlgbmxg1m44xb520nsqw45)/orcontent.aspx?inc = about.htm. Accessed 22 Aug 2006.
Topkis, D.M. 1998. Supermodularity and complementarity. Princeton: Princeton University Press.
von Neumann, J. 1937. A model of general economic equilibrium. In Ergebnisse eines mathematischen Kolloquiums 8, ed. K. Menger [in German]. Trans. as ‘A model of general equilibrium’. Review of Economic Studies 13(1945–6): 1–9.
Walras, L. 1883. Théorie mathématique de la richesse sociale. Lausanne: Corbaz.
Wolfe, P. 1959. The simplex method for quadratic programming. Econometrica 27: 382–398.
Author information
Authors and Affiliations
Editor information
Copyright information
© 2018 Macmillan Publishers Ltd.
About this entry
Cite this entry
Vertinsky, I. (2018). Operations Research. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_1370
Download citation
DOI: https://doi.org/10.1057/978-1-349-95189-5_1370
Published:
Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-95188-8
Online ISBN: 978-1-349-95189-5
eBook Packages: Economics and FinanceReference Module Humanities and Social SciencesReference Module Business, Economics and Social Sciences