AN APPROXIMATE METHOD FOR LOCAL OPTIMA FOR NONLINEAR MIXED INTEGER PROGRAMMING-PROBLEMS

Abstract

For a nonlinear 0-1 integer programming problem with constraint set X = (x1,...,x(n)), we first add new constraints [GRAPHICS] to the constraint set, thus to convert the integer problem into a nonlinear programming problem. Then we utilize a modified penalty function method to solve this nonlinear program to obtain a local optima Running the proposed method by a widely commercialized nonlinear program software shows that this method is more convenient than current approaches as branch-and-bound method and implicit enumeration method. One issue remained for studies is to expand this method into a global method by systematically generating suitable starting points then to perform optimization processes from each of these points.