concept

nonlinear programming

Also known as: NLP, LP

Facts (8)

Sources

Comprehensive framework for smart residential demand side ... nature.com Nature Mar 22, 2025 5 facts

claimNonlinear programming (LP) and mixed integer nonlinear programming (MINLP) optimizations are applied to the nonlinear mathematical formulation of the Residential Demand Side Management (RDSM) problem, though they involve higher computational complexity compared to linear models.

claimRecent research suggests that prominent methods for demand-side management include linear programming, nonlinear programming, dynamic programming, stochastic programming, robust optimization, fuzzy logic, metaheuristic or evolutionary optimization, artificial neural networks, and game theory.

claimNonlinear programming (LP) and mixed integer nonlinear programming (MINLP) optimizations are applied to the nonlinear mathematical formulation of Residential Demand Side Management (RDSM) problems.

claimProminent methods suggested in recent research for demand-side management include linear programming, nonlinear programming, dynamic programming, stochastic programming, robust optimization, fuzzy logic, metaheuristic or evolutionary optimization, artificial neural networks, and game theory.

A comprehensive overview on demand side energy management ... link.springer.com Springer Mar 13, 2023 3 facts

referenceDeterministic methods used in energy management to reduce electricity consumption include linear programming (LP), nonlinear programming (NLP), gradient base (GB), Lagrangian algorithms, Lagrange–Newton, interior point method, Lyapunov techniques, and mixed integer nonlinear programming (MINP).

claimIn the context of energy management optimization, NLP stands for Nonlinear programming.

referenceDeterministic methods used in energy management to reduce electricity consumption include Linear Programming (LP) (Erol-Kantarci and Mouftah 2011; Zhu et al. 2012), Nonlinear Programming (NLP) (Althaher et al. 2015), Gradient Base (GB) (Huang et al. 2015), Lagrangian algorithms (Boyd; Gatsis and Giannakis 2011), Lagrange–Newton (Dong et al. 2012), Interior Point Method (Samadi et al. 2012), Lyapunov techniques (Guo et al. 2012), and Mixed Integer Nonlinear Programming (MINP) (Behrangrad et al. 2010).