We all constantly optimize: our schedules, our investments, our taxes. We do very few of these optimizations on a computer. There are, however, many businesses that make heavy use of advanced hardware and software to optimize their operations; it is estimated that more than 75% of all number-crunching is spent on that. This may not seem so surprising if one considers the pervasiveness of optimization problems and their computational demand. To optimize the flight and crew scheduling of a
major airline or to distribute electricity on the nation's system of power plants and high-voltage lines is a major effort, and it has to be done continually. Optimization is not limited to scheduling tasks. Many
challenging problems need to be solved in engineering science such as optimization of an aircraft's shape or of the reentry maneuver of a returning space shuttle.
  For somewhat over a year now we maintain two webpages that have become fixtures on the Web for people in search of optimization software, from students who may have their first encounter with the subject to major companies from all over the globe. The numerous commercial vendors of software do a good deal of advertising themselves. There is, however, high-quality software available, frequently developed by university researchers, which is free for research purposes and even available to
business for free or at moderate cost. One problem is to locate it, another is to test it. Both require expertise and some effort. Reward for this work so far has been its acknowledgment through the frequent
accesses of the webpages, their citation in publications, as well as  consulting contracts.
  There is also a collection of own software available which compared  so well to even some of the commercial products that it is downloaded many times each day by academic and commercial "clients". On the other hand, many of the codes tested have been improved by their authors as a direct result of the benchmark testing performed. All of this would not have been possible with the same ease and efficiency without the World Wide Web. Every Spring semester students in a graduate class first learn the mathematical background and then utilize this information for projects preparing them for work on the leading edge of computational optimization. Several, in fact, made contact again after accepting jobs
in industry while others do related consulting work as a summer job.
  The titles and URLs are:
Decision Tree for Optimization Software:  http://plato.la.asu.edu/guide.html Benchmarks for Optimization Software:     http://plato.la.asu.edu/bench.html