Applications of Optimal Multiprocesses

Abstract

In a previous paper a theory of necessary conditions for optimal multiprocess problems was supplied, that is, problems in dynamic optimization involving a collection of control systems coupled through constraints on the endpoints of the trajectories and the cost functions. Here the scope of the new theory is illustrated by application to optimization problems in investment planning, impulse control, optics, robotics, and renewable resources.