Proximal point algorithms for multi-criteria optimization with the difference of convex objective functions

DOI10.1007/s10957-015-0847-0zbMath1342.90175OpenAlexW2175228355MaRDI QIDQ289089

Robert de Souza, Ying Ji, Mark Goh

Publication date: 27 May 2016

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-015-0847-0

zbMATH Keywords

critical pointportfolio optimizationproximal point algorithmmulti-criteria optimizationDC

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Multi-objective and goal programming (90C29)

Related Items

Bundle-based descent method for nonsmooth multiobjective DC optimization with inequality constraints, Non-monotonous sequential subgradient projection algorithm for convex feasibility problem, A parameterized proximal point algorithm for separable convex optimization, A proximal point method for difference of convex functions in multi-objective optimization with application to group dynamic problems

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• An interior proximal method in vector optimization
• A proximal point-type method for multicriteria optimization
• Optimality conditions for D.C. vector optimization problems under reverse convex constraints
• Multiobjective DC programs with infinite convex constraints
• A global optimization using linear relaxation for generalized geometric programming
• Global Optimization of the Scenario Generation and Portfolio Selection Problems
• Monotone Operators and the Proximal Point Algorithm
• Proximal Methods in Vector Optimization
• Proximité et dualité dans un espace hilbertien
• Convex Analysis