Algorithm for locating the extremum of a multi-dimensional constrained function and its application to the PPPL Hybrid Study

A description is presented of a general algorithm for locating the extremum of a multi-dimensional constrained function. The algorithm employs a series of techniques dominated by random shrinkage, steepest descent, and adaptive creeping. A discussion follows of the algorithm's application to a ''real world'' problem, namely the optimization of the price of electricity, P/sub eh/, from a hybrid fusion-fission reactor. Upon the basis of comparisons with other optimization schemes of a survey nature, the algorithm is concluded to yield a good approximation to the location of a function's optimum.