Global optimization for signomial discrete programming problems in engineering design

This paper proposes a novel method to solve signomial discrete programming (SDP) problems frequently occurring in engineering design. Various signomial terms are first convexified following different strategies. The original SDP program is then converted into a convex integer program solvable by commercialized packages to obtain globally optimal solutions. Compared with current SDP methods, the proposed method is guaranteed to converge to a global optimum, is computationally more efficient, and is capable of treating zero boundary problems. Numerical examples are presented to demonstrate the usefulness of the proposed method in engineering design.