Joint chance-constrained optimization problems under discrete distributions arise frequently in financial management and business operations. These can be reformulated as mixed-integer programs. The size of integer programs is usually very large even though the original problem medium size. This paper studies an augmented Lagrangian decomposition method for finding high-quality feasible solutio...

In this paper, a chattering-free sliding-mode control is mainly proposed in a second-order discrete-time system. For achieving this purpose, firstly, a suitable control law would be derived by using the discrete-time Lyapunov stability theory and the sliding-mode concept. Then the input constraint is taken into account as a saturation function in the proposed control law. In order to guarantee ...

We examine the convexity and tractability of the two-sided linear chance constraint model under Gaussian uncertainty. We show that these constraints can be applied directly to model a larger class of nonlinear chance constraints as well as provide a reasonable approximation for a challenging class of quadratic chance constraints of direct interest for applications in power systems. With a view ...

Motivated by a class of chance-constrained optimization problems, we explore modifications of the (generalized) Benders’ decomposition approach. The chance-constrained problems we consider involve a random variable with an underlying discrete distribution, are convex in the decision variable, but their probabilistic constraint is neither separable nor linear. The variants of Benders’ approach w...

In this paper, the problem of stability, recursive feasibility and convergence conditions stochastic model predictive control for linear discrete-time systems affected by a large class correlated disturbances is addressed. A that guarantees convergence, average cost bound chance constraint satisfaction developed. The results rely on computation probabilistic reachable invariant sets using notio...

Despite comprehensive literature works on developing fitness-based optimization algorithms, their performance is yet challenged by constraint handling in various engineering tasks. The present study, concerns the widely-used external penalty technique for sizing design of pin-jointed structures. Observer-teacher-learner-based optimization is employed here since previously addressed by a number ...