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Optimal Power Flow Using Moth-Flame Optimizer Implementation

https://doi.org/10.2139/ssrn.4760595
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Optimal power flow with voltage stability improvement and loss reduction in power system using Moth-Flame Optimizer
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Solution of the optimal power flow problem considering security constraints using an improved chaotic electromagnetic field optimization algorithm
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Particle swarm optimization with an aging leader and challengers algorithm for the solution of optimal power flow problem
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Optimal reactive power dispatch solution by loss minimization using moth-flame optimization technique
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Tree-seed algorithm for solving optimal power flow problem in large-scale power systems incorporating validations and comparisons
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Applications of multi-objective dimension-based firefly algorithm to optimize the power losses, emission, and cost in power systems
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An efficient particle swarm optimization algorithm to solve optimal power flow problem integrated with FACTS devices
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Application of modified pigeon-inspired optimization algorithm and constraint-objective sorting rule on multi-objective optimal power flow problem
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Wolf-pack (Canis lupus) hunting strategies emerge from simple rules in computational simulations
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Application of chaotic krill herd algorithm for optimal power flow with direct current link placement problem
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A modified teaching–learning based optimization for multi-objective optimal power flow problem
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A novel multi-objective hybrid particle swarm and salp optimization algorithm for technical-economical-environmental operation in power systems
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Optimal power flow using moth swarm algorithm
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Multi-objective harmony search algorithm for optimal power flow problem
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GSA: A Gravitational Search Algorithm
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Application of imperialist competitive algorithm with its modified techniques for multi-objective optimal power flow problem: A comparative study
inferredcites →https://doi.org/10.1016/j.swevo.2012.09.002openalex-extracted
S-shaped versus V-shaped transfer functions for binary Particle Swarm Optimization
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Use of a self-adaptive penalty approach for engineering optimization problems
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Measuring exploration/exploitation in particle swarms using swarm diversity
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Principal components analysis by the galaxy-based search algorithm: a novel metaheuristic for continuous optimisation
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Swarm Intelligence from Natural to Artificial Systems: Ant Colony Optimization
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