Solving a Global-Mixed Integer Signomial Geometric Fractional Programming Problem

Abstract

This article addresses mixed integer fractional signomial geometric programming (MIFSGP) prob
lems, which have been widely used in industrial design. In this paper, first, we convert fractional signomial
 programming into a nonfractional problem so that it maintains its geometric structure. Then, convex relaxation
 is used to reach a mixed integer global solution. Although, in many cases, we obtain a better objective function
 value with this process, designers may still be dissatisfied with the rupture between the original objective func
tion value and the relaxed value. Therefore, we apply a spatial branch and bound algorithm to decrease that
 distance to an acceptable extent and maintain the global solution. Finally, a real design problem is considered
 to evaluate the efficiency and accuracy of the proposed technique.

DOI: 10.5281/zenodo.14880138