Proximal point algorithms for convex multi-criteria optimization with applications to supply chain risk management

DOI10.1007/s10957-014-0540-8zbMath1302.90202OpenAlexW2008533031MaRDI QIDQ481062

Tie-Nan Wang, Shao-Jian Qu, Mark Goh, Robert de Souza

Publication date: 12 December 2014

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

Full work available at URL: https://doi.org/10.1007/s10957-014-0540-8

zbMATH Keywords

multi-criteria optimizationPareto optimumsupply chain risk managementproximate point algorithms

Mathematics Subject Classification ID

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

Related Items (4)

A new algorithm for linearly constrained c-convex vector optimization with a supply chain network risk application ⋮ Sources of uncertainty and risk quantification methods in supply chain management: a literature study ⋮ Nonmonotone gradient methods for vector optimization with a portfolio optimization application ⋮ Proximal point algorithms for vector DC programming with applications to probabilistic lot sizing with service levels

Cites Work

• Quasi-Newton methods for solving multiobjective optimization
• An implementable proximal point algorithmic framework for nuclear norm minimization
• Convergence of the projected gradient method for quasiconvex multiobjective optimization
• An interior proximal method in vector optimization
• Multi-criteria decision analysis via ratio and difference judgement
• Nonlinear multiobjective optimization
• Multiobjective DC programs with infinite convex constraints

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