Search Results - (( evolution optimization modified algorithm ) OR ( storage optimization method algorithm ))
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A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…This modified algorithm called Modified Multi-Objective Particle Swarm Optimization (M-MOPSO) employs a fixed-sized external archive along with a dynamic boundary-based search mechanism to evolve the population. …”
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A refined differential evolution algorithm for improving the performance of optimization process
Published 2011“…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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Improved chemotaxis differential evolution optimization algorithm
Published 2015“…The social foraging behavior of Escherichia coli has recently received great attention and it has been employed to solve complex search optimization problems.This paper presents a modified bacterial foraging optimization BFO algorithm, ICDEOA (Improved Chemotaxis Differential Evolution Optimization Algorithm), to cope with premature convergence of reproduction operator.In ICDEOA, reproduction operator of BFOA is replaced with probabilistic reposition operator to enhance the intensification and the diversification of the search space.ICDEOA was compared with state-of-the-art DE and non-DE variants on 7 numerical functions of the 2014 Congress on Evolutionary Computation (CEC 2014). …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications
Published 2023“…Carbon; Decarbonization; Electric energy storage; Fossil fuels; Global warming; Renewable energy resources; Carbon emissions; Decarbonisation; Energy storage system; Method; Microgrid; Optimal energy; Optimization algorithms; Sizing; Storage systems; System sizings; Cost effectiveness…”
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Optimal allocation of battery energy storage system using whale optimization algorithm
Published 2023“…Battery storage; Electric batteries; Battery energy storage systems; Firefly algorithms; Loss reduction; Meta-heuristic methods; Optimal allocation; Optimization algorithms; Overall system loss reduction; Performance; System loss; Whale optimization algorithm; Particle swarm optimization (PSO)…”
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Optimization algorithms for energy storage integrated microgrid performance enhancement
Published 2023“…Controllers; Electric power transmission; Electric power utilization; Energy management systems; Energy resources; Energy storage; Iterative methods; Learning algorithms; Microgrids; Operating costs; Particle swarm optimization (PSO); Scheduling; Scheduling algorithms; Stochastic systems; Storage management; Two term control systems; Charge-discharge; Day-ahead; Distributed Energy Resources; Microgrid; Optimization algorithms; Optimized controllers; Optimized scheduling; Performance enhancements; Scheduling controllers; Storage systems; Energy management…”
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Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals
Published 2012“…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm
Published 2016“…In this paper, a modified Cuckoo searching algorithm is proposed to solve the multiple objective Green Logistics optimization problem. …”
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Grey Wolf Optimizer Based Battery Energy Storage System Sizing for Economic Operation of Microgrid
Published 2023Conference Paper -
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Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables
Published 2025Subjects:Article -
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Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems
Published 2015“…To achieve this objective, an iterative approach based on swarm intelligence is used to find the optimal CQI threshold at which the competing criteria are optimized. …”
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A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…So, the travelling distance, power consumption and lifetime of the network will be calculated in both cases for original algorithm and modified algorithm, which is a modified deployment algorithm, and compared between them. …”
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A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization
Published 2018“…M-MOPSO is compared with four other algorithms namely, MOPSO, Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm based on Decompositions (MOEA/D) and Multi-Objective Differential Evolution (MODE). …”
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Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm
Published 2024“…By iteratively modifying the control settings to achieve optimal performance, the DE algorithm replaces the requirement for manual PID tuning, which can be time-consuming and suboptimal. …”
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Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm
Published 2024“…By iteratively modifying the control settings to achieve optimal performance, the DE algorithm replaces the requirement for manual PID tuning, which can be time-consuming and suboptimal. …”
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