The operations research literature contains numerous studies on the design and application of optimization and heuristic solution procedures. These studies identify a particular optimization problem, suggest a general solution procedure, and then customize that procedure to improve its efficiency and/or accuracy. In contrast, this paper shows how to use existing solution procedures more effectively. We develop a methodology for predicting the relative performance of alternative procedures, using easily computed problem characteristics. This methodology enables us, for any given data set, to preselect a solution procedure. We apply this preselection methodology to the 0-1 knapsack problem for which two successful optimization procedures, dynamic programming and branch-and-search, are available. Extensive computational testing indicates that substantial savings in average computation time are achieved. The benefits of our work include faster and cheaper identification of effective solution procedures, as well as an improved understanding of the relationship between problem characteristics and the performance of various procedures. Our methodology can be applied to many optimization problems to develop easily implemented guidelines for selecting appropriate solution procedures.

Marc E. Posner is a Professor of Operations Research in the Integrated Systems Engineering Department at The Ohio State University. He received a B.A. in Mathematics from Brandeis University, an M.S. and Ph.D. in Operations Research from the University of Pennsylvania. He has published in most of the major operations research journals on a variety of topics ranging from the construction of statistical decision rules to the decomposition of nonlinear programming problems. His research is primarily in the field of deterministic optimization with an emphasis on integer programming. He is interested both in heuristic and exact methods. An area of focus is scheduling and production problems. Currently, he is a Departmental Editor in Scheduling and Logistics for IIE Transactions and is an Associate Editor for Naval Research Logistics.

Nicholas G. Hall is Professor of Management Sciences in the Fisher College of Business at The Ohio State University. He holds B.A., M.A. degrees in economics from the University of Cambridge, a professional qualification in accounting, and a Ph.D. (1986) from the University of California at Berkeley. His research interests are in operational supply chain issues, especially scheduling and pricing, and in applications of operations research to public policy problems. He is the author of over 70 refereed publications, and has given over 240 academic presentations, including 88 invited presentations in 20 countries, 6 conference keynote presentations and 6 INFORMS tutorials. He won the Faculty Research Award of the Fisher College of Business in 1998 and 2005. His teaching interests include project management, supply chain operations, decision modeling, and dynamic programming courses. He served as President of Manufacturing and Service Operations Management Society (1999–2000), and Vice President for Membership and Professional Recognition of INFORMS (2001–2003). He continues to serve on the editorial boards of the journals Operations Research (1991-) and Management Science (1993-). He has served on several INFORMS committees, including: Nicholson Prize (1997-1999), Finance (2001-2007), Practitioner and Practice Activities (2000) and Expository Writing (2007-2009), and organized six national and international conference clusters including 58 technical sessions. His research is currently funded by grants from the National Science Foundation and EPSRC (the national scientific funding agency of the U.K.). He is the owner and founder of a consulting company, CDOR, that serves the Ohio business and government communities.