It comes at a time when complexity research has grown in stature to both attract critics as well as proponents armed with ample evidence that conventional economic theory, for example, fails to predict either the direction or magnitude of U.S. interest-rate swings. The mere fact that SFI's leader asks such questions may be one reason the Business Network's membership grew 60 percent in the past year to fifty-three companies. Of course, another explanation for the rise is SFI's growing stature among academicians as the nation's leader in complexity research. Plenty, it seems. One of the liveliest discussions at the one-day meeting involved the development and use of genetic algorithms, or GAs, as they are more often called.
Scheduling is one of many applications of GAs.
After the 1970s and 1980s shakeout in the farm-equipment industry, Deere laid off thousands of workers and razed older plants in the face of a steep downturn in demand caused by declining farm income. The company remodeled its remaining plants and switched to incentives that rewarded the performance of teams of workers. After Fulkerson learned about SFI's research on complexity theory and genetic algorithms, he convinced Deere executives to fund development of a prototype system incorporating GAs to schedule the remodeled Moline, Illinois, seed-planter manufacturing plant. At the same time, plant managers are not SFI regulars and no Deere plant manager could be expected to assume the risk of incorporating a GA into his or her facility. To overcome that hurdle, Fulkerson convinced engineering managers at the John Deere Technical Center to assume the risk.