A mean-absolute deviation-skewness portfolio optimization model
Annals of Operations Research
Bilinear separation of two sets in n-space
Computational Optimization and Applications
Multiplicative programming problems: analysis and efficient point search heuristic
Journal of Optimization Theory and Applications
Solving a class of multiplicative programs with 0–1 knapsack constraints
Journal of Optimization Theory and Applications
Outcome-space cutting-plane algorithm for linear multiplicative programming
Journal of Optimization Theory and Applications
A Finite Branch-and-Bound Algorithm for Linear Multiplicative Programming
Computational Optimization and Applications
Monotonic Optimization: Problems and Solution Approaches
SIAM Journal on Optimization
Journal of Global Optimization
Heuristic Methods for Linear Multiplicative Programming
Journal of Global Optimization
Journal of Global Optimization
On finding most optimal rectangular package plans
DAC '82 Proceedings of the 19th Design Automation Conference
Global Optimization of Multiplicative Programs
Journal of Global Optimization
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This article presents a finite branch-and-bound algorithm for globally solving general linear multiplicative programming problems (GLMP). The proposed algorithm is based on the recently developed theory of monotonic optimization. The proposed algorithm provides a nonisolated global optimal solution, and it turns out that such an optimal solution is adequately guaranteed to be feasible and to be close to the actual optimal solution. It can be shown by the numerical results that the proposed algorithm is effective and the computational results can be gained in short time.