11 citations · 39 across the 13 of their papers we have counts for
6 papers · 1 filter
Solution of Robust Linear Optimization Problems
Parthasarathi Mondal, Akshay Kumar Ojha
Robust optimization(RO) is an important tool for handling optimization problem with uncertainty. The main objective of RO is to solve optimization problems due to uncertainty assoc…
Feasibility Conditions of Robust Portfolio Solutions under Single and Combined Uncertainties
Pulak Swain, Akshay Kumar Ojha
In this paper, we derive the feasibility conditions for the robust counterparts of the uncertain Markowitz model. Our study is based on ellipsoidal, box, polyhedral uncertainty set…
Robust Portfolio Optimization under Ambiguous Chance Constraints
Pulak Swain, Akshay Kumar Ojha
In this paper, we discuss the ambiguous chance constrained based portfolio optimization problems, in which the perturbations associated with the input parameters are stochastic in…
Chance Constrained Robust Portfolio Optimization when the Perturbations Follow Normal and Exponential Distributions
Pulak Swain, Akshay Kumar Ojha
In this paper, we consider the chance constrained based uncertain portfolio optimization problem in which the uncertain parameters are stochastic in nature. The primary goal of the…
Uncertain random geometric programming problems
Tapas Mondal, Akshay Kumar Ojha, Sabyasachi Pani
In this paper, we introduce a deterministic formulation for the geometric programming problem, wherein the coefficients are represented as independent linear-normal uncertain rando…
Geometric Programming Problems with Triangular and Trapezoidal Two-fold Uncertainty Distributions
Tapas Mondal, Akshay Kumar Ojha, Sabyasachi Pani
Geometric programming (GP) is a well-known optimization tool for dealing with a wide range of nonlinear optimization and engineering problems. In general, it is assumed that the pa…