Search Results - (( loading optimization approach algorithm ) OR ( using evolutionary method algorithm ))
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A decomposition/aggregation method for solving electrical power dispatch problems
Published 2023“…Subsequently, the solutions from the areas are combined (aggregated) to solve the overall system problem. The results obtained using the decomposition / aggregation method are compared with the results found when the ED Problem was solved using a centralised EP approach and the base-case results found from solving a (non-optimal) load flow. …”
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Optimal finite- time prescribed performance of servo pneumatic positioning with PID control tuning using an evolutionary mating algorithm
Published 2023“…This paper presents an optimum tuning on finite-time prescribed performance with PID (FT-PPC-PID) controller using the Evolutionary Mating Algorithm (EMA) approach for a pneumatic servo system’s (PSS) rod-piston positioning. …”
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A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm
Published 2015“…To solve the multi-objective OPF problem, Pareto optimal method is used to form the Pareto optimal set. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025“…Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2024“…Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar
Published 2017“…Comparison on solving the energy management problem using RHED approach with metaheuristic methods like PSO and evolutionary programming (EP) was also conducted and found that RHED approach provides the optimal solution with less computational run time. …”
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Thesis -
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…These steps have conducted using the MEMPHA model and ROA algorithm to optimize three metrics: execution time, total communication volume, and imbalance ratio (load balancing). …”
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Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad
Published 2016“…Backtracking search algorithm (BSA) as the new evolutionary technique of optimization is used for solving the problems. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…In this paper, the important issues related with the best input variable selection for a hybrid model is addressed. A hybrid approach that combines ANN and an evolutionary optimization technique, genetic algorithm (GA) is used for the development of a short term load forecast (STLF) model. …”
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Computational intelligence method for optimal rotary design system
Published 2008“…The core ideas behind using computation, evolutionary computation and fuzzy logic techniques are presented, along with a selection of specific real-world applications. …”
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Effect of multi-unit and multi-type DG installation using integrated optimization technique in distribution power system planning
Published 2025“…This technique employs a hybrid approach that combines elements of immune algorithms, moth flame optimization, and evolutionary programming to achieve more accurate and efficient results. …”
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Environmentally constraint economic dispatch and reactive power planning for ensuring secure operation in power system / Elia Erwani Hassan
Published 2015“…The comprehensive analyses were also conducted between two other familiar optimization methods known as original Bacterial Foraging Optimization (BFO) algorithm and Meta heuristic Evolutionary Programming (Meta-EP). …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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Design of digital circuit structure based on evolutionary algorithm method
Published 2008“…Evolutionary Algorithms (EAs) cover all the applications involving the use of Evolutionary Computation in electronic system design. …”
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Modeling and optimization of cold extrusion process by using response surface methodology and metaheuristic approaches
Published 2018“…Subsequently, the analytical approach and metaheuristic algorithms, specifically the particle swarm optimization, cuckoo search algorithm (CSA) and flower pollination algorithm, were applied to optimize the extrusion process parameters. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications
Published 2026“…Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
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