| Abstract: | Two optimal control problems typically encountered in bioengineering studies are solved using five dynamic optimization algorithms carefully selected from among the most widely recognized gradient-based algorithms. All the problems are solved using a medium-sized mainframe computer. The convergence characteristics of each algorithm are tested by using them to solve each of the two problems. It is recognized that a number of difficulties arise with these larger problems. Some of these problems include prohibitive storage requirements and large computational times. The consequences of the choice of any specific algorithm for solving typical dynamic optimization problems in biomedicine are pointed out. |
