collaborators

5 papers

math.OC2025

A Three-Operator Splitting Scheme Derived from Three-Block ADMM

Anshika Anshika, Jiaxing Li, Debdas Ghosh +1

This work presents a new three-operator splitting method to handle monotone inclusion and convex optimization problems. The proposed splitting serves as another natural extension o…

math.OC2025

Nonmonotone Trust-Region Methods for Optimization of Set-Valued Mapping of Finite Cardinality

Suprova Ghosh, Debdas Ghosh, Zai-Yun Peng +1

Non-monotone trust-region methods are known to provide additional benefits for scalar and multi-objective optimization, such as enhancing the probability of convergence and improvi…

math.OC2025

Robust Optimization Approach for Solving Uncertain Multiobjective Optimization Problems Using the Projected Gradient Method

Shubham Kumar, Nihar Kumar Mahatoa, Debdas Ghosh

Numerous real-world applications of uncertain multiobjective optimization problems (UMOPs) can be found in science, engineering, business, and management. To handle the solution of…

math.OC2025

Global Convergence and Rate Analysis of the Steepest Descent Method for Uncertain Multiobjective Optimization via a Robust Optimization Approach

Shubham Kumar, Nihar Kumar Mahato, Debdas Ghosh

In this article, we extend our previous work (Applicable Analysis, 2024, pp. 1-25) on the steepest descent method for uncertain multiobjective optimization problems. While that stu…

math.OC2025

Solution of Uncertain Multiobjective Optimization Problems by Using Nonlinear Conjugate Gradient Method

Shubham Kumar, Nihar Kumar Mahato, Debdas Ghosh

This paper introduces a nonlinear conjugate gradient method (NCGM) for addressing the robust counterpart of uncertain multiobjective optimization problems (UMOPs). Here, the robust…