OPERATIONS RESEARCH informs Vol. 58, No. 4, Part 2 of 2, July–August 2010, pp. 1035–1036 ® issn 0030-364X eissn 1526-5463 10 5804 1035 doi 10.1287/opre.1100.0842 © 2010 INFORMS Preface to the Special Issue on Computational Economics Kenneth Judd Revolution and Peace, Hoover Institution on War, Stanford, California 94305,
[email protected] Garrett van Ryzin Graduate School of Business, Columbia University, New York, New York 10027,
[email protected] Economics is thestudy of how scarceresourcesareallo- Costs,” by Schulz and Uhan, looks at thecomplexityof cated. Operations research studies how to accomplish goals computing theleastcorevaluein cooperativegameswith in the least costly manner. These fields have much to offer supermodular cost structures. Such games arise in a variety each other in terms of challenging problems that need to of operations research problems—scheduling, for example. be solved and the techniques to solve them. This was the Theauthors show that such problemsarestrongly NP hard, caseafterWorld War II, partly becausetheindividuals who but for a special case of single-machine scheduling the went on to be the leading scholars in economics and oper- Shapleyvalueis in theleastcore. ations research worked together during WWII. In fact, the “Multigrid Techniques in Economics,” by Speight, is a two fields share many early luminaries, including Arrow, good example of how advances in computational physics, Dantzig, Holt, Kantorovich, Koopmans, Modigliani, Scarf, in this casecomputational fluid dynamics, can beapplied and von Neumann. Unfortunately, as new generations of to economic problems. Multigrid methods are a relatively scholars took charge, those ties weakened, resulting in lit- new approach to solving partial differential equations, and tle interaction between operations research scholars and this paper explains how they can be applied to dynamic economists in the past three decades.