This talk will look at two aspects of genetic algorithms: some scientific application case studies and the role of parallel computing. The first part of the talk will survey several genetic algorithm application projects the author has been involved in. These applications include airline crew scheduling, molecular docking, parameter fitting in a quantum chemistry model, and VLSI circuit recognition. The second part of the talk will discuss aspects of parallel computing as they relate to GAs, in particular, the influence of the parallel computer architecture and programming model on the choice of GA algorithm. We will conclude with a description of PGAPack, a freely-distributed parallel genetic algorithm library.

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1996-1997 Mathematics in High Performance Computing