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The Great Salmon Run Algorithm


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Salmon swimming upstream to spawn.

Researchers are using an algorithm based on the experiences of salmon swimming upstream to spawn to help them find optimal solutions to specific problems.

Credit: q13Fox.xom

Babol University of Technology researchers have developed an algorithm based on the survival trials faced by salmon swimming upstream to the spawning grounds to help them find the optimal solution to a given problem.

Bio-inspiration has been widely used in problem solving, as genetic algorithms take the best solutions, randomly modify them, and test them again. Repeating this process enables scientists to find an optimal answer through a process similar to survival of the fittest in nature.

However, the Babol researchers determined a genetic algorithm would not handle certain engineering problems in which many constraints on plausible solutions must be applied. They developed the great salmon run (TGSR) algorithm as a simulation of the actual salmon run, enabling the researchers to identify specific solutions to a problem that are optimal in the sense of reaching the spawning grounds.

The researchers say they have successfully applied the TGSR algorithm to 25 standard benchmarking problems in engineering. "In most cases, the TGSR algorithm worked better than the other methods," the researchers say. "Moreover, for some problems, it was quicker at converging on an optimal solution."

From EurekAlert
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