In this paper, the method of admixture chance constrained programming was researched in order to deal with the uncertainties in the complex systems. The concept of the grey uncertain programming was ...

Discover how multiple objective stochastic linear programming can address practical problems like portfolio selection and water resource management. Explore the limitations and solutions in this ...

\title[CP]{Stochastic optimization\\Chance constrained programming} \author[Fabian Bastin]{Fabian Bastin \\ \url{[email protected]} \\ Université de Montréal -- CIRRELT -- IVADO -- Fin ... A ...

This paper presents a novel joint chance-constrained dynamic programming algorithm, which explicitly bounds the probability of failure to satisfy given state constraints. Existing constrained dynamic ...

Uncertainty in the parameters of an optimization problem has a large impact on the outcome of the optimization results. Intuitionistic fuzzy chance constrained programming (IFCCP) is one technique ...

This repository contains the implementation of Conformal Predictive Programming for Chance Constrained Optimization. We will walk you through how to use the codes in this repository for your own ...

Kaplan, Robert S., Mark Eisner, and John Soden. "Admissible Decision Rules for the E-Model of Chance-Constrained Programming." Management Science 17 (January 1971): 337–353 ...

In this paper, we resort to the bounded rationality principle to introduce satisfying solution for multiobjective stochastic linear programming problems. These solutions that are based on the ...