concept

optimization algorithms

Also known as: Optimization methods, Optimization algorithms, optimization algorithm

Facts (21)

Sources

A comprehensive overview on demand side energy management ... link.springer.com Springer Mar 13, 2023 8 facts

claimThe search criteria for the study included articles matching the keywords 'Demand Side Management', 'Demand Response', 'Load categorization', 'Optimization methods', 'Customer classification', and 'Distributed Energy Sources integration'.

claimThe research questions addressed by the paper include: identifying solutions for Demand Side Management (DSM) implementation problems in smart grids, identifying popular optimization methods in DSM, and determining how DSM policies and methods affect peak demand and power costs.

referenceVardakas JS, Zorba N, and Verikoukis CV published a survey on demand response programs in smart grids, covering pricing methods and optimization algorithms, in 2014.

referenceVardakas JS, Zorba N, and Verikoukis CV conducted a survey on demand response programs in smart grids, focusing on pricing methods and optimization algorithms, published in 2014.

claimThe load profile of consumer appliances is crucial for developing consumer-specific optimization algorithms that account for individual comfort preferences.

procedureThe search strategy for the literature review utilized Boolean operators ('AND', 'OR') to combine keywords including 'Demand Side Management', 'Demand Response', 'Load categorization', 'Optimization methods', 'Customer classification', and 'Distributed Energy Sources integration'.

referencePanda et al. (2022) assert that advanced optimization algorithms must be developed to enable efficient energy consumption scheduling and reduce dynamic tariffs, thereby preserving customer satisfaction and improving system cost efficiency.

referenceAdvanced optimization algorithms are required to enable efficient energy consumption scheduling and reduce dynamic tariffs while maintaining customer satisfaction and system cost efficiency, as noted by Panda et al. (2022).

Overcoming the limitations of Knowledge Graphs for Decision ... xpertrule.com XpertRule 3 facts

claimComposite AI incorporates optimization algorithms that allow it to solve problems involving complex constraints and objective functions, which Knowledge Graphs cannot do.

claimKnowledge Graphs are unsuited for tasks that involve finding optimal solutions within constrained environments because they lack the necessary optimization algorithms.

claimKnowledge Graphs lack built-in optimization algorithms and mechanisms for representing and enforcing complex constraints.

Neuro-Symbolic AI: Explainability, Challenges, and Future Trends arxiv.org arXiv Nov 7, 2024 2 facts

procedureThe implicit adjustment process in Deep Symbolic Regression (DSR) provides feedback to the RNN to guide expression generation, relying on gradient descent or optimization algorithms to adjust RNN weights.

procedureThe LNN-based inductive logic programming method proposed by Sen et al. (2022) operates through the following procedure: (1) Input a knowledge base containing facts, relations, and rules describing the target structure. (2) Build an LNN network based on the template to simulate logical connectives, where each node represents an expression or logical rule. (3) Use facts in the knowledge base as training data to adjust logical operations via optimization algorithms like back propagation and gradient descent. (4) Convert the trained LNN into a set of logical rules that reflect the relationships in the input data.

Demand side management using optimization strategies for efficient ... journals.plos.org PLOS ONE Mar 21, 2024 2 facts

referenceShami T. M., Grace D., Burr A., and Mitchell P. D. introduced the 'Single candidate optimizer' as a novel optimization algorithm in a 2022 paper in Evolutionary Intelligence.

referenceJasim A. M., Jasim B. H., Neagu B.-C., and Alhasnawi B. N. authored 'Efficient Optimization Algorithm-Based Demand-Side Management Program for Smart Grid Residential Load' published in Axioms in December 2022.

Comprehensive framework for smart residential demand side ... nature.com Nature Mar 22, 2025 2 facts

claimThe integration of electric vehicles into demand-side management frameworks has driven extensive research into optimization algorithms, grid resilience, renewable energy microgrid feasibility, and smart energy management.

Advancing energy efficiency: innovative technologies and strategic ... oaepublish.com OAE Publishing 1 fact

referenceAlimohamadi and Jahangir proposed retrofitting existing buildings in Iran using optimization algorithms and tools like MATLAB and EnergyPlus, while considering local economic factors such as energy pricing and subsidies.

Building Trustworthy NeuroSymbolic AI Systems - arXiv arxiv.org arXiv 1 fact

claimOptimization algorithms and attention methods in Large Language Models can attempt to induce fake behavior, and if rewards are not unique to the task, the model will have difficulty aligning with desired behaviors (Shah et al. 2022a).

A Comprehensive Review of Neuro-symbolic AI for Robustness ... link.springer.com Springer Dec 9, 2025 1 fact

referenceChen et al. (2023) demonstrated the symbolic discovery of optimization algorithms.

A Comprehensive Review on Residential Demand Side Management ideas.repec.org MDPI 1 fact

referenceMakhadmeh et al. published a survey titled 'Optimization methods for power scheduling problems in smart home' in the journal Renewable and Sustainable Energy Reviews in 2019.