Knowledge Tree
Home Research Docs About
concept

mixed-integer linear programming

Also known as: MILP, mixed-integer programming, mixed-integer linear programming, mixed-integer linear programming models

Related (1)

Facts (15)

Sources
A comprehensive overview on demand side energy management ... link.springer.com Springer Mar 13, 2023 7 facts
claimIn the context of energy management optimization, MILP stands for Mixed integer linear programming.
referenceOptimization techniques proposed to enhance the scheduling of distributed energy sources include mixed-integer linear programming (MILP) (Erdinc et al. 2014), two-stage robust optimization (Liu and Hsu 2018), and heuristic optimization (Luo et al. 2018).
referenceSou KC, Weimer J, Sandberg H, and Johansson KH utilized mixed integer linear programming to schedule smart home appliances, presented at the 2011 IEEE Conference on Decision and Control and European Control Conference.
referenceAmini M, Frye J, Ilić MD, and Karabasoglu O presented the paper 'Smart residential energy scheduling utilizing two stage mixed integer linear programming' at the 2015 North American Power Symposium.
referenceOptimization techniques proposed to enhance the scheduling of distributed energy sources include mixed-integer linear programming (MILP) (Erdinc et al. 2014), two-stage robust optimization (Liu and Hsu 2018), and heuristic optimization (Luo et al. 2018).
claimAmini M, Frye J, Ilić MD, and Karabasoglu O developed a smart residential energy scheduling method utilizing two-stage mixed-integer linear programming in 2015.
referenceSou KC, Weimer J, Sandberg H, and Johansson KH presented a method for scheduling smart home appliances using mixed integer linear programming at the 2011 50th IEEE Conference on Decision and Control and European Control Conference.
Comprehensive framework for smart residential demand side ... nature.com Nature Mar 22, 2025 6 facts
claimLinear programming (LP) and mixed integer linear programming (MILP) approaches fail to provide satisfactory results as the complexity of the Residential Demand Side Management (RDSM) problem increases, despite being easy to implement and providing quick responses.
claimLinear programming (LP) and mixed integer linear programming (MILP) methods are applied to mathematical model formulations in energy systems to represent linear relationships between system variables with an objective of cost minimization while considering equality and inequality constraints.
claimLinear programming (LP) and mixed integer linear programming (MILP) approaches for Residential Demand Side Management (RDSM) problems fail to provide satisfactory results as the complexity of the problem increases, despite being easy to implement and providing quick responses.
claimLinear programming (LP) and mixed integer linear programming (MILP) approaches for Residential Demand Side Management (RDSM) problems fail to provide satisfactory results as the complexity of the problem increases, despite being easy to implement and providing quick responses.
claimLinear programming (LP) and mixed integer linear programming (MILP) methods are applied to mathematical model formulations in energy systems to minimize costs while considering equality and inequality constraints, representing a linear relationship between system variables.
claimLinear programming (LP) and mixed integer linear programming (MILP) methods are applied to mathematical model formulations in energy systems to represent linear relationships between system variables with an objective of cost minimization, while considering equality and inequality constraints.
Track: Poster Session 3 - aistats 2026 virtual.aistats.org Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche · AISTATS 1 fact
perspectiveYilin Xie, Shiqiang Zhang, Joel Paulson, and Calvin Tsay investigate mixed-integer programming (MIP) as a paradigm for global acquisition function optimization in Bayesian optimization, noting that most existing algorithms use sampling- or gradient-based methods that do not provably converge to global optima.
A critical review on techno-economic analysis of hybrid renewable ... link.springer.com Springer Dec 6, 2023 1 fact
procedureResearchers investigated the economic performance of combined heat and power systems for residential applications using iterative approaches, specifically mixed-integer linear programming models and heuristic techniques such as genetic algorithms (GA) and particle swarm optimization (PSO).