A relaxed projection method for solving multiobjective optimization problems
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DOI: 10.1016/j.ejor.2016.05.026
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Cited by:
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- Glaydston Carvalho Bento & Sandro Dimy Barbosa Bitar & João Xavier Cruz Neto & Antoine Soubeyran & João Carlos Oliveira Souza, 2020.
"A proximal point method for difference of convex functions in multi-objective optimization with application to group dynamic problems,"
Computational Optimization and Applications, Springer, vol. 75(1), pages 263-290, January.
- Glaydston de Carvalho Bento & Sandro Dimy Barbosa Bitar & João Xavier da Cruz Neto & Antoine Soubeyran & João Carlos de Oliveira Souza, 2020. "A proximal point method for difference of convex functions in multi-objective optimization with application to group dynamic problems," Post-Print hal-02351104, HAL.
- Kerkhove, L.-P. & Vanhoucke, M., 2017. "A parallel multi-objective scatter search for optimising incentive contract design in projects," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1066-1084.
- Morovati, Vahid & Pourkarimi, Latif, 2019. "Extension of Zoutendijk method for solving constrained multiobjective optimization problems," European Journal of Operational Research, Elsevier, vol. 273(1), pages 44-57.
- Qu, Shaojian & Ji, Ying & Jiang, Jianlin & Zhang, Qingpu, 2017. "Nonmonotone gradient methods for vector optimization with a portfolio optimization application," European Journal of Operational Research, Elsevier, vol. 263(2), pages 356-366.
- Xiaopeng Zhao & Markus A. Köbis & Yonghong Yao & Jen-Chih Yao, 2021. "A Projected Subgradient Method for Nondifferentiable Quasiconvex Multiobjective Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 190(1), pages 82-107, July.
- Kabgani, Alireza & Soleimani-damaneh, Majid, 2022. "Semi-quasidifferentiability in nonsmooth nonconvex multiobjective optimization," European Journal of Operational Research, Elsevier, vol. 299(1), pages 35-45.
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Keywords
Multiple objective programming; Pareto optimality; Projected subgradient method;All these keywords.
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