Solving large parameter optimization problems using genetic algorithms
Kalmanje S. Krishnakumar, Ram Swaminathan, Sanjay Garg, S. Narayanaswamy · Guidance, Navigation and Control Conference · 1995
We consider Genetic Algorithm (GA) variations that are suitable for solving optimization problems with a large number of parameters. For effective genetic search, these problems require an enormously large number of function evaluations. The variations presented essentially keep the string lengths as small as possible while maintaining good sampling of the search space. This facilitates lower number of function evaluations for finding an optimal solution. We apply the techniques to a difficult test function and to an optimization problem concerning the partitioned Integrated Flight Propulsion Controller (IFPC) design.