Digital Darwin

It’s a jungle out there. So businesses of every kind are increasingly turning to software rooted in survival-ofthe-fittest strategies to solve extraordinarily complex problems like managing air traffic, optimizing the efficiency of service calls, and even creating new materials and food flavors.

Software based on so-called genetic algorithms is “showing up in every way, shape, and form” in the business world, says Stephanie Forrest, a professor of computer science at the University of New Mexico. Genetic algorithms create a group of solutions to a particular problem-say, how to reschedule a fleet of airplanes when a thunderstorm shuts down a major airport. The algorithms rapidly replicate, mutate, and produce new generations of possible solutions that yield better and better results, all with very little human intervention. Millions of solutions might be created, but like fish eggs drifting in the sea, most will die. A solution that is better than its competitors eventually emerges.

It’s an approach that has been kicking around academic circles for years and has yielded some practical applications, but it is only now finding widespread commercial adoption. “Finally, this technology is coming out of the geeky environment and is being provided as a business solution,” says Navi Radjou, a principal analyst at Forrester Research in Cambridge, MA.

The list of businesses using evolutionary software is expanding. For example, Delta Airlines this year signed on with a company that develops genetic algorithms, Ascent Technology of Cambridge, MA, to optimize the schedules of many of its employees-one of the biggest individual jobs ever undertaken by this type of software. Delta’s objective is to cut costs without reducing its level of service. And that’s a survival strategy that might have impressed Darwin himself.

Sampling of Competitors
Company Technology
Ascent Technology (Cambridge, MA) Evolutionary software to optimize airport and airline operations
IBM Research (Hawthorne, NY) Large-scale, self-managing, self-repairing computer systems
NuTech Solutions (Charlotte, NC) Evolutionary software that competes to solve problems from traffic-light coordination to artificial-flavor development
RDI (London and Cambridge, England) Evolutionary software to optimize drug combinations for HIV treatment
Tripos (St. Louis, MO) Genetic algorithms that speed drug development

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