Author

Debdas Ghosh

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Open access Sep 2026

Projected quasi-subgradient method for Hölder continuous quasi-convex multiobjective optimization

We propose a projected quasi-subgradient method for constrained, nondifferentiable, quasi-convex multiobjective minimization problems. Unlike existing approaches that rely on Lipschitz continuity, our method only requires Hölder continuity of the objective components, thereby covering a broader class of quasi-convex fu...

F. Babu, Debdas Ghosh, Muzaffar Sarkar Raju · Positivity (Dordrecht) · 0 citations

Preprint Jul 2026

Hager-Zhang Conjugate Gradient Method for Set Optimization with Set-Valued Objective Map of Finite Cardinality

This work introduces a nonlinear Hager-Zhang conjugate gradient method for solving set optimization problems. The objective function under consideration is defined by a finite collection of continuously differentiable functions. Notably, the proposed approach imposes restrictions neither on the existence of a finite ge...

Ravi Raushan, Debdas Ghosh, Zai-Yun Peng · 0 citations

Preprint Jul 2026

Proximal Gradient Methods for Unconstrained Set Optimization Problems with Set-Valued Maps of Finite Cardinality

The convergence analysis of the proximal gradient method with line search provides a theoretical advancement over the convergence results previously established for the steepest descent method in set-valued optimization problems.

Ravi Raushan, Debdas Ghosh, Anshika et al. · 0 citations