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Business Week Special Report: "Optimization Software," October 30, 2000, pp. 174B-174H.
This issue features two articles under the banner, "Industrial Management." Both provide overview of operations research applied to SCM, supply chain management. "New software using data from the supply chain is saving companies billions."
Perhaps the first formal, quantitative method for optimization was the "simplex algorithm" developed by George Danzig shortly after World War II. This is the basis for most "linear programming" models to solve optimization problems. This method is the heart of such programs as the Solver in Microsoft's Excel spreadsheet, providing an optimization tool within reach of nearly everyone.
Optimization problems include:
Business Week's interview with Saul Gass, U. of Maryland is titled "Making Decisions with Precision," which certainly caught my eye. Prof. Gass (whose PhD advisor was George Danzig) defines operations research (often called management science) as "the application of the methods of science, mostly mathematics and statistics, to complex problems arising in the direction and management of large systems of people, machines, materials, and money in industry, business, government, and defense. Basically, it is a scientific method for providing a basis for making a decision."
Neither article mentions optimization under uncertainty. This greatly increases the computation effort, typically from 100-1000 times. Monte Carlo simulation approximates the solutions as if probability distributions could be carried through the calculations. Fortunately, computers continue to improve. Both Crystal Ball (www.decisioneering.com) and @RISK (www. palisade.com) feature optimization features or add-ins to provide stochastic optimization. Also, both tools are available in versions that will make a local area network of PCs behave like a large parallel computer.
John Schuyler, October 2000.
Copyright © 2000 by John R. Schuyler. All rights reserved. Permission to copy with reproduction of this notice.