Stochastic programming is a framework for modeling optimization problems that involve uncertainty. Unlike deterministic optimization problems, where all parameters are known with certainty, stochastic ...
ABSTRACT: This paper considers multiobjective integer programming problems involving random variables in constraints. Using the concept of simple recourse, the formulated multiobjective stochastic ...
ABSTRACT: The economic emission dispatch (EED) problem minimizes two competing objective functions, fuel cost and emission, while satisfying several equality and inequality constraints. Since the ...
This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...