Theory and applications of a nonconvex programming algorithm

Abstract

In this thesis, a solution technique to solve a class of nonlinear programming problems is presented. The problem considered is the minimization of separable concave functions and linear functions over linear polyhedra. A branch-and-bound algorithm for identifying an optimal solution is described; it is equivalent to the solution of a finite sequence of linear programming problems. Computational results are cited fbr a computer code developed implementihg the algorithm. The algorithm is applied to dynamic capacity expansion problem considering single plant-singie commodity, multi-plant-single commodity, and multi-plant-multi commodity cases.