Discrete Applied Mathematics - Discrete applied mathematics in Japan
Linear multiplicative programming
Mathematical Programming: Series A and B
Primal-relaxed dual global optimization approach
Journal of Optimization Theory and Applications
Solving multiple-objective problems in the objective space
Journal of Optimization Theory and Applications
Multiplicative programming problems: analysis and efficient point search heuristic
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
Journal of Optimization Theory and Applications
Generalized Convex Multiplicative Programming via QuasiconcaveMinimization
Journal of Global Optimization
Journal of Global Optimization
Heuristic Methods for Linear Multiplicative Programming
Journal of Global Optimization
Analysis of Bounds for Multilinear Functions
Journal of Global Optimization
A Finite Algorithm for a Class of Nonlinear Multiplicative Programs
Journal of Global Optimization
Global Optimization of Multiplicative Programs
Journal of Global Optimization
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
An outcome space approach for generalized convex multiplicative programs
Journal of Global Optimization
An objective space cut and bound algorithm for convex multiplicative programmes
Journal of Global Optimization
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Global optimization problems involving the minimization of a product of convex functions on a convex set are addressed in this paper. Elements of convex analysis are used to obtain a suitable representation of the convex multiplicative problem in the outcome space, where its global solution is reduced to the solution of a sequence of quasiconcave minimizations on polytopes. Computational experiments illustrate the performance of the global optimization algorithm proposed.