Adaptive Dynamic Programming (ADP) has emerged as a powerful framework for the design of optimal control policies in nonlinear dynamical systems, particularly when precise mathematical models are ...

Global optimization of nonlinear mixed-integer programming (MINLP) addresses decision problems in which some variables are constrained to take integer values, while the objective function or ...

Abstract: In this paper, demand response problems are discussed based on mixed integer nonlinear programming. The considered demand response problems are defined as multi objective nonlinear ...

In the era of A.I. agents, many Silicon Valley programmers are now barely programming. Instead, what they’re doing is deeply, deeply weird. Credit...Illustration by Pablo Delcan and Danielle Del Plato ...

Electrodialysis (ED) presents a competitive method for desalinating brackish waters. Herein we perform cost optimization of a single-stack ED system across a range of feed salinities and water ...

Functional programming, as the name implies, is about functions. While functions are part of just about every programming paradigm, including JavaScript, a functional programmer has unique ...

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained ...

In this tutorial, we will look at some basic theory of random dynamical systems, defined by non-linear stochastic differential equations with an underlying graph structure. The concrete application I ...

ABSTRACT: The aim of this paper is to reduce the losses, total generation cost by switching of transmission line and to maintain voltage security under N- 1 contingency conditions. Generation cost is ...