William W. Cooper
|2006||Impact Prize : Winner(s) [+show more]|
Data Envelopment Analysis (DEA) was first described in the article "Measuring the efficiency of decision-making units," European Journal of Operational Research, by A. Charnes, W. Cooper, and E. Rhodes (1978). It was selected as one of the 30 most influential papers published in the first 30 years of that journal.
Researchers and practitioners in many fields have recognized DEA’s power and ease of use as a method for evaluating the performance of operational processes. DEA has been successfully applied in many organizations world-wide, including hospitals, HMO’s, military units, universities, cities, courts, investment portfolio managers, and logistics and manufacturing firms. DEA helps identify peak performers in these organizations and suggests ways for the others to improve.
DEA’s novel mathematical-programming-based, data-oriented approach has also been helpful in comparing the economies of nations and regions, due to its particularly effective means of accounting for the conversion of multiple inputs to multiple outputs.
Charnes and Cooper required very few assumptions in the development of DEA, so it has opened up possibilities for use in cases that were resistant to other OR approaches. For example, DEA helped improve pupil transportation in North Carolina, saving over 50 million dollars. This application was a finalist for the 1993 Edelman Prize.
Abraham Charnes and William Cooper’s decades-long friendship and collaboration ended with Dr. Charnes' death in 1992. Both have been inducted into the IFORS' Operational Research Hall of Fame. For their seminal work on DEA, INFORMS is delighted to award the 2006 Impact Prize to Abraham Charnes and William W. Cooper.
|1982||John von Neumann Theory Prize: Winner(s) [+show more]|
The citation reads as follows:
These contributions, many of them linked to the awardees' common association with what is now the Carnegie-Mellon University, span a multitude of fields including: linear programming and inequalities, goals and chance-constrained programming, geometric programming, infinite dimensional and convex programming, network modeling and analysis, fractional and interval programming, prediction and stochastic decision rules, and game theory. This body of work is notable not only for its significance and breadth, but also for its exemplification of the power of broadly conceived applications to spark the advance of theory by first-rate minds.