An enhanced operator-oriented genetic search algorithm used to solve nonlinear dynamic control problems

An order-based enhanced operator oriented genetic algorithm (EOOGA) is used to find solutions to nonlinear dynamic control type problems. Solutions are expressed as a sequence of decision vectors that result in near optimal performance. The algorithm is tested on a satellite trajectory problem. The results are compared to randomly generated solutions, and solutions obtained using dynamic programming.