A mean-absolute deviation-skewness portfolio optimization model
Annals of Operations Research
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
Heuristic Methods for Linear Multiplicative Programming
Journal of Global Optimization
On Covering Methods for D.C. Optimization
Journal of Global Optimization
Finding GM-estimators with global optimization techniques
Journal of Global Optimization
A Unified Monotonic Approach to Generalized Linear Fractional Programming
Journal of Global Optimization
Global Optimization of Multiplicative Programs
Journal of Global Optimization
A new efficient algorithm based on DC programming and DCA for clustering
Journal of Global Optimization
A method of acceleration for a class of multiplicative programming problems with exponent
Journal of Computational and Applied Mathematics
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This paper presents a deterministic global optimization algorithm for solving generalized linear multiplicative programming (GLMP). In this algorithm, a new linearization method is proposed, which applies more information of the function of (GLMP) than some other methods. By using this new linearization technique, the initial nonconvex problem is reduced to a sequence of linear programming problems. A deleting rule is presented to improve the convergence speed of this algorithm. The convergence of this algorithm is established, and some experiments are reported to show the feasibility and efficiency of this algorithm.