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Research on Optimal Dispatching of Multi-Microgrid Considering Economy
Published 2018-10-01“…Combined with a specific example, the algorithm is used to solve the economic optimal scheduling problem of single micro-grid and multi-micro-grid, and the cost of power generation under two grid connection modes was compared. …”
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222
Presenting a multi-objective decision-making model for cost-time trade-off considering the time value of money and solving it using particle swarm optimization
Published 2024-08-01“…This model assists project managers in gaining better insight into cost-time impacts, optimizing resource allocation, and ultimately improving project performance by reducing delays.…”
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223
Optimization of power output in plateau photovoltaic power stations using a hybrid Kepler and Gaussian quantum particle swarm algorithm
Published 2025-07-01“…The proposed solution integrates the Kepler Optimization Algorithm (KOA) with the Gaussian Quantum Improved Particle Swarm Optimization (GQPSO) to address multi-objective optimization, with the goal of maximizing power generation, minimizing operational costs, and enhancing system stability. …”
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224
An application of Arctic puffin optimization algorithm of a production model for selling price and green level dependent demand with interval uncertainty
Published 2025-07-01“…Furthermore, seven other algorithms (Dandelion Optimizer (DO), Grey wolf optimizer (GWO), The whale optimization algorithm (WOA), Artificial electric field algorithm (AEFA), Harris hawks optimization (HHO), Multi-verse optimizer (MVO) and Slime mould algorithm (SMA)) are used to compare the obtained solution from APO. …”
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Optimization Strategy of Microgrid Hierarchical Scheduling Considering Electric Vehicles User Satisfaction Degree
Published 2020-12-01“…Renewable energy is used to support the load of the microgrid in the source storage layer, and the excess part is absorbed by the dispatchable electric vehicle, which makes the comprehensive cost of the microgrid minimized. The improved ant lion algorithm is used to solve the model of the source storage layer. …”
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228
An Improved Marriage in Honey-Bee Optimization Algorithm for Minimizing Earliness/Tardiness Penalties in Single-Machine Scheduling with a Restrictive Common Due Date
Published 2025-01-01“…This study evaluates the efficiency of a swarm intelligence algorithm called marriage in honey-bee optimization (MBO) in solving the single-machine weighted earliness/tardiness problem, a type of NP-hard combinatorial optimization problem. …”
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Application of improved ant-lion algorithm for power systems.
Published 2024-01-01“…The required number of iterations was significantly better than other algorithms. In the verification of solving economic load dispatch, the improved ant-lion optimizer achieved a total fuel cost reduction of 0.10% -2.39% and 6% in both 3-unit and 6-unit simulations, respectively, compared to the other three algorithms. …”
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231
Research on a hybrid deep learning model based on two-stage decomposition and an improved whale optimization algorithm for air quality index prediction
Published 2025-12-01“…The model's hyperparameters are optimized by the Improved Whale Optimization Algorithm (IWOA), which improves search efficacy by including chaotic mapping, a nonlinear shrinkage factor, and a Levy flight strategy. …”
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Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization
Published 2025-01-01“…Its objective is to identify the most optimal features in a dataset by eliminating redundant data while preserving the highest possible classification accuracy. …”
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234
Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering
Published 2024-05-01“…Separate optimization of weighting processing for each frequency channel can significantly improve the average efficiency characteristics of a multichannel Doppler filter and eliminate all the shortcomings of the classical and modified FFT algorithms when processing non-equidistant pulse sequences. …”
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235
Logarithmic mean optimization a metaheuristic algorithm for global and case specific energy optimization
Published 2025-05-01“…In a real-world application, LMO was employed to optimize a hybrid photovoltaic (PV) and wind energy system, achieving a 5000 kWh energy yield at a minimized cost of $20,000, outperforming all other algorithms in both efficiency and effectiveness. …”
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236
Optimal Computation Offloading Decisions Based on System Utility and Cost Balance
Published 2025-01-01“…By calculating the full load rate of edge server clusters, we describe and evaluate the operational efficiency of the system, aiming to design a computation offloading decision scheme that not only reduces costs, but also enhances system utility. Based on the new evaluation model, an objective function is constructed to minimize the system’s cost-utility ratio, and an improved particle swarm optimization algorithm with enhanced search capabilities is proposed to solve it by designing a computation offloading strategy. …”
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237
Illustration Design Model with Clustering Optimization Genetic Algorithm
Published 2021-01-01“…This paper proposes an illustration art design model based on operator and clustering optimization genetic algorithm. First, during the operation of the genetic algorithm, the values of the crossover probability and the mutation probability are dynamically adjusted according to the characteristics of the population to improve the search efficiency of the algorithm, then the k-medoids algorithm is introduced to optimize the clustering of the genetic algorithm, and a cost function is used to carry out and evaluate the quality of clustering to optimize the complexity of the original algorithm. …”
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238
Variance Reduction Optimization Algorithm Based on Random Sampling
Published 2025-03-01“…The main feature of the algorithm including an inner and outer double loop structure is designed: the outer loop structure uses mini-batch random samples to calculate the gradient, approximating the full gradient and reducing the gradient calculation cost; the inner loop structure also uses mini-batch random samples to calculate the gradient and replace the single sample random gradient, improving convergence stability of the algorithm. …”
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239
Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm
Published 2025-04-01“…For the prediction of VIV parameters, the Random Forest model is the most effective. The RMSE values of the improved optimal algorithm are 0.017, 0.026, and 0.295, and the R<sup>2</sup> values are 0.9421, 0.8875, and 0.9462. …”
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240
Adaptive crayfish optimization algorithm for multi-objective scheduling optimization in distributed production workshops
Published 2025-06-01“…Furthermore, an improved crowding distance calculation enhances the algorithm’s performance in multi-objective optimization by improving solution distribution. …”
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