Solving fractional multicriteria optimization problems with sum of squares convex polynomial data

DOI10.1007/s10957-018-1222-8zbMath1390.90532OpenAlexW2792013195MaRDI QIDQ1743539

Jae Hyoung Lee, Liguo Jiao

Publication date: 13 April 2018

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

Full work available at URL: https://doi.org/10.1007/s10957-018-1222-8

zbMATH Keywords

semidefinite programmingfractional programmingmulticriteria optimizationsum of square convex polynomials

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Semidefinite programming (90C22) Multi-objective and goal programming (90C29) Fractional programming (90C32)

Related Items (10)

Optimality and duality in nonsmooth composite vector optimization and applications ⋮ Finding efficient solutions in robust multiple objective optimization with SOS-convex polynomial data ⋮ Multi-objective optimization problems with SOS-convex polynomials over an LMI constraint ⋮ A new scheme for approximating the weakly efficient solution set of vector rational optimization problems ⋮ A utopia point method-based robust vector polynomial optimization scheme ⋮ On solving a class of fractional semi-infinite polynomial programming problems ⋮ A hybrid approach for finding efficient solutions in vector optimization with SOS-convex polynomials ⋮ Optimality conditions for minimax optimization problems with an infinite number of constraints and related applications ⋮ Multi-objective convex polynomial optimization and semidefinite programming relaxations ⋮ Existence of Pareto solutions for vector polynomial optimization problems with constraints

Uses Software

• CVX

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