This paper develops global optimization algorithms for linear multiplicative and generalized linear multiplicative programs based upon the lower bounding procedure of Ryoo and Sahinidis  and new greedy branching schemes that are applicable in the context of any rectangular branch-and-bound algorithm. Extensive computational results are presented on a wide range of problems from the literature, including quadratic and bilinear programs, and randomly generated large-scale multiplicative programs. It is shown that our algorithms make possible for the first time the solution of large and complex multiplicative programs to global optimality.
- Greedy branching
- Multiplicative programs
ASJC Scopus subject areas
- Computer Science Applications
- Control and Optimization
- Management Science and Operations Research
- Applied Mathematics