Search Results - ((solution optimization) OR (evolution optimization)) techniques
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Performance comparison of differential evolution and particle swarm optimization in constrained optimization
Published 2012“…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…ECHT is considered to be a flagship ensemble technique till date for constrained optimization problems, whereas SRDE employs a parent selection mechanism for constrained optimization. …”
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Optimal HE-PWM inverter switching patterns using differential evolution algorithm
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Enabling more optimality and adaptability to the dynamic nature of CDTO, we propose a novel Variable-Length multi-objective Whale optimization Integrated with Differential Evolution designated as VL-WIDE for joint cloudlet deployment and tasks offloading. …”
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Decomposition–based multi-objective differential evolution for extractive multi-document automatic text summarization
Published 2024“…However, the current approach faces a significant hurdle due to the computational intensity of the process, particularly when employing complex optimization techniques like swarm intelligence optimization alongside a costly ATS repair operator. …”
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Energy efficiency improvement of an unbalanced electrical distribution system based on the conservative voltage reduction in tandem with the optimal capacitors placement and sizing...
Published 2015“…The DEPSO is designed based on the amalgamation of particle swarm optimization (PSO) and differential evolution (DE) that serves as a new mutation technique responsible to provide a new population with improved sizing and location of capacitors. …”
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Energy efficiency improvement of an unbalanced electrical distribution system based on the conservative voltage reduction in tandem with the optical capacitors placement and sizin...
Published 2015“…The DEPSO is designed based on the amalgamation of particle swarm optimization (PSO) and differential evolution (DE) that serves as a new mutation technique responsible to provide a new population with improved sizing and location of capacitors. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…Also, fed batch fermentation problems in winery wastewater treatment and biogas generation from sewage sludge are developed for optimization. Though DE traditionally performs better than other evolutionary algorithms and swarm intelligence techniques in optimization of fed-batch fermentation, BSA edged DE and other recent metaheuristics to emerge as superior optimization method in this work. …”
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Modification of species-based differential evolution for multimodal optimization
Published 2015“…Differential Evolution (DE), is a random search technique using vectors as an alternative solution in the search for the optimum. …”
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Hybrid Harmony Search Algorithm Integrating Differential Evolution and Lévy Flight for Engineering Optimization
Published 2025“…This paper proposes HSA-DELF, a novel hybrid algorithm that combines differential evolution (DE) and Lévy flight (LF) techniques to enhance the performance of HSA. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…Unlike existing OBL-based techniques, the PMT generates more than one candidate in multiple solution-space directions. …”
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Hybrid Harmony Search Algorithm Integrating Differential Evolution and Lévy Flight for Engineering Optimization
Published 2025“…This paper proposes HSA-DELF, a novel hybrid algorithm that combines differential evolution (DE) and Lévy flight (LF) techniques to enhance the performance of HSA. …”
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Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization
Published 2024“…The current approach encounters a significant hurdle due to the long execution time, especially when employing complex optimization techniques alongside a computationally expensive ATS repair operator that repairs multiple candidate solutions. …”
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The superiority of feasible solutions-moth flame optimizer using valve point loading
Published 2024“…The MFO, Grey Wolf Optimizer (GWO), Success-history-based Parameter Adaptation Technique of Differential Evolution - Superiority of Feasible Solutions (SHADE-SF), and Superiority of Feasible Solutions-Moth Flame Optimizer (SF-MFO) algorithms are applied to address the OPF problem with two objective functions: (1) reducing energy production costs and (2) minimizing power losses. …”
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A novel cell-selection optimization handover for long-term evolution (LTE) macrocellusing fuzzy TOPSIS
Published 2016“…In this method, we use an integrated fuzzy technique for order preference by using similarity to ideal solution (TOPSIS) on S-criterion, availability of resource blocks (RBs), and uplink signal-to-interference-plus-noise ratio. …”
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Optimizing of PID controller for flexible link system using a Pareto-based Multi-objective differential (PMODE) evolution
Published 2011“…This can be viewed like many other real-life control problems as a multi-objectives optimization problem in which an optimal compromise between the design objectives is required. …”
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Midrange exploration exploitation searching particle swarm optimization in dynamic environment
Published 2021“…However, conventional Particle Swarm Optimization still has limitations in finding the optimal solution in a dynamic environment. …”
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A novel clustering based genetic algorithm for route optimization
Published 2016“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. In addition, the introduction of dynamic population control with polygamy selection processes enabled fast convergence to optimal solution and diversity in the population respectively.…”
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