Optimal Integration of Renewable Energy–Based Distributed Generation Units in Radial Distribution System by Le Chi Kien, Truong Van Hien, Hoang Do Ngoc Tram, Thai Dinh Pham

“…Besides, this research also proposes a novel meta-heuristic optimization algorithm called revised coyote optimization algorithm (RCOA) for addressing the optimization problems of the simultaneous integration of DGUs in IEEE 69-bus radial distribution system. …”
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Prediction and dynamic optimization of drilling performance based on the combination of mineral composition and operational factors by Xiong Xiuli, Li Qian, Liu Junhao, Jiang Jie

“…According to the training and testing results, the introduction of mineral composition can effectively improve the training speed and testing accuracy. Through the established prediction function, a dynamic optimization algorithm combined with DOE (Design of Experiments) theory was also developed. …”
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A VNS-NPGA approach to multi-objective optimization of hub-and-spoke logistics network by Changxi Ma, Chuwei Shi, Yun Yang, Yongpeng Zhao, Zhuye Xu, Bo Du

“…To realize low-cost freight transport in the logistics network and improve the network operation efficiency, a multi-objective optimization model and the corresponding algorithm for a hub-and-spoke logistics network are proposed based on the multi-level location of hub points and channels layout. …”
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Optimizing TCP Performance in Multi-AP Residential Broadband Connections via Minislot Access by Domenico Giustiniano, Eduard Goma, Alberto Lopez Toledo, George Athanasiou

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Optimizing urban energy flows: Integrative vehicle-to-building strategies and renewable energy management by Jian Hern Yeoh, Kai-Yun Lo, I-Yun Lisa Hsieh

“…Although the inclusion of ESS incurs higher initial costs, it significantly improves peak load management by an additional 14.11%. …”
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Improving the Fast Fourier Transform for Space and Edge Computing Applications with an Efficient In-Place Method by Christoforos Vasilakis, Alexandros Tsagkaropoulos, Ioannis Koutoulas, Dionysios Reisis

“…The execution of inputs ranging from 1K to 16K FFT points, using 8-bit or 16-bit as FP or BFP numbers, on the space-proven Atmel AVR32 and Vision Processing Unit (VPU) Intel Movidius Myriad 2, the edge device Raspberry Pi Zero 2W and a low-cost accelerator on Xilinx Zynq 7000 Field Programmable Gate Array (FPGA), validates the method’s performance improvement.…”
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Multi-Objective Optimization of Insulation Thickness with Respect to On-Site RES Generation in Residential Buildings by Agis M. Papadopoulos, Konstantinos Polychronakis, Elli Kyriaki, Effrosyni Giama

“…This paper investigates the optimization of insulation thickness with respect to the integration of renewable energy systems in residential buildings in order to improve energy efficiency, maximize the contribution of renewables and reduce life cycle costs. …”
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Enhancing Sustainable Manufacturing in Industry 4.0: A Zero-Defect Approach Leveraging Effective Dynamic Quality Factors by Rouhollah Khakpour, Ahmad Ebrahimi, Seyed Mohammad Seyed Hosseini

“…The methodology follows these steps:</p> <p style="text-align: left;">Step 1: Analysing effective dynamic factors of product quality</p> <p style="text-align: left;">Step2: Evaluating Triple Bottom Line (TBL) criteria</p> <p style="text-align: left;">Step 3: Measuring current sustainability state</p> <p style="text-align: left;">Step 4: Implementing ZDM strategies</p> <p style="text-align: left;">Step 5: Measuring improvements in sustainability</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;"><strong>Results</strong></p> <p style="text-align: left;">&nbsp;<strong>Effects</strong> <strong>of Single Unit Defective Product on TBL Sustainability State in Value Stream</strong></p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">Summary of current sustainability state</p> <table style="float: left;" width="479"> <tbody> <tr> <td width="64"> <p>Product model</p> </td> <td width="56"> <p>Daily schedule (set)</p> </td> <td width="61"> <p>Defective product rate (%)</p> </td> <td width="58"> <p>Number of defective products (set)</p> </td> <td width="85"> <p>Environmental sustainability</p> <p>State</p> </td> <td width="78"> <p>Social sustainability</p> <p>state</p> </td> <td width="78"> <p>Economic sustainability</p> <p>state</p> </td> </tr> <tr> <td width="64"> <p>Refrigerator</p> </td> <td width="56"> <p>480 set</p> </td> <td width="61"> <p>3%</p> </td> <td width="58"> <p>15</p> </td> <td width="85"> <p>Wasted material: 15 set</p> <p>&nbsp;</p> <p>Wasted energy: 239.25 kwh</p> </td> <td width="78"> <p>Waste of manpower: 1650 pmin</p> </td> <td width="78"> <p>Wasted costs:</p> <p>3265.65 $</p> </td> </tr> </tbody> </table> <p style="text-align: left;"><strong>&nbsp;</strong></p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">Future TBL sustainability state</p> <table style="float: left;" width="486"> <tbody> <tr> <td width="67"> <p>Product model</p> </td> <td width="59"> <p>Daily schedule (set)</p> </td> <td width="56"> <p>Defective product rate (%)</p> </td> <td width="16"> <p>&nbsp;</p> </td> <td width="61"> <p>Number of defective products (set)</p> </td> <td width="83"> <p>Environmental sustainability</p> <p>state</p> </td> <td width="82"> <p>Social sustainability state</p> </td> <td width="62"> <p>Economic sustainability state</p> </td> </tr> <tr> <td width="67"> <p>Refrigerator</p> </td> <td width="59"> <p>480 set</p> </td> <td width="56"> <p>0.2%</p> </td> <td width="16"> <p>&nbsp;</p> </td> <td width="61"> <p>1</p> </td> <td width="83"> <p>Wasted material: 1 set</p> <p>&nbsp;</p> <p>Wasted energy: 15.95 kwh</p> </td> <td width="82"> <p>Waste of manpower: 110 pmin</p> </td> <td width="62"> <p>Wasted costs:</p> <p>217.71 $</p> </td> </tr> </tbody> </table> <p style="text-align: left;"><strong>&nbsp;</strong></p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;"><strong>Discussion and conclusion</strong></p> <p style="text-align: left;">&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Implementing the proposed approach aimed at achieving zero-defect products and enhancing TBL sustainability as its ultimate goal has provided valuable insights for practitioners and tangible improvements in the case study of this research. …”
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Metamodel-Based Optimization Method for Traffic Network Signal Design under Stochastic Demand by Wei Huang, Xuanyu Zhang, Haofan Cheng, Jiemin Xie

“…By incorporating the model bias, the combined metamodel can better approximate the original optimal solution. Moreover, incorporating the gradient information of the traffic flow in the optimization search algorithm can further improve the solution performance. …”
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Source-storage-load optimization control technology of DC microgrid with virtual energy storage by WANG Chang, JIANG Yu, FU Shouqiang, SHU Yinan, ZHANG Xiangyu

“…On this basis, under the coordinated control of source and storage of DC microgrid, particle swarm optimization algorithm is used to optimize the design of virtual capacitance values in different periods of time to improve the economic benefits of the system. …”
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RFID‐Based Enhanced Resource Optimization for 5G/6G Network Applications by Stella N. Arinze, Augustine O. Nwajana

“…This study provides a scalable, cost‐effective solution for optimizing resource management in 5G and lays the groundwork for future advancements in 6G networks. …”
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Coordinated Optimal Dispatch of Distribution Grids and P2P Energy Trading Markets by Jing Deng, Fawu He, Qingbin Zeng, Jie Yan, Rangxiong Liu, Dongsheng He, Song Zhou

“…To address the nonlinear, high‐dimensional optimization challenges, an improved Convex‐Soft Actor‐Critic (C‐SAC) algorithm is developed, combining deep reinforcement learning with convex optimization to achieve privacy‐preserving distributed coordination. …”
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Advanced Control Technique for Optimal Power Management of a Prosumer-Centric Residential Microgrid by Peter Anuoluwapo Gbadega, Yanxia Sun, Olufunke Abolaji Balogun

“…To solve the multi-objective power management optimization problem, the Teaching-Learning-Based Optimization (TLBO) algorithm was implemented. …”
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Hummingbird-Inspired Modified Particle Swarm Optimization for Efficient Task Scheduling in Cloud Computing by Longyang Du, Qingxuan Wang

“…Comparative experiments conducted on synthetic and real-world datasets (HPC2N) with diverse task loads demonstrate measurable performance improvements, including up to 18% better resource utilization, up to a 35% decrease in imbalance degree, and up to a 20% improvement in execution cost compared to recent algorithms. …”
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A Day-Ahead Optimal Battery Scheduling Considering the Grid Stability of Distribution Feeders by Umme Mumtahina, Sanath Alahakoon, Peter Wolfs

“…This study presents a comprehensive framework for optimizing energy management systems by integrating advanced methodologies for weather forecasting, energy cost analysis, and grid stability using a mixed-integer linear programming (MILP) algorithm. …”
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An Improved Diagnosis Approach for Short-Circuit Fault Diagnosis in MPC-Based Current Source Inverter System by Jonggrist Jongudomkarn, Pirat Khunkitti, Apirat Siritaratiwat

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Optimization Study of PVT Coupled Water Loop Heat Pump Energy Supply System by Lv Tiangang, Liu Bing, Wu Jun, Zhu Li, Hou Jingxuan

“…By employing the Hooke-Jeeves algorithm, the system's design and operation parameters were optimized with annual cost and system COP as objective functions. …”
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Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation by Ankit Garg, K. R. Niazi, Shubham Tiwari, Sachin Sharma, Tanuj Rawat

“…The optimization model is solved using the Modified Water Evaporation algorithm. …”
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Analysis of Smart Grid Optimal Scheduling considering the Demand Response of Different EV Owners by Xiaohua Zhang, Chongyang Liao, Xingrui Chen, Kuiheng Deng, Bolin Chen, Yibo Gong

“…Compared to previous studies, the proposed classified scheduling method exhibits significant improvements in terms of revenue maximization, load distribution among different types of EVs, generation cost savings, and load variance reduction.…”
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A Hierarchical Evolutionary Search Framework with Manifold Learning for Powertrain Optimization of Flying Vehicles by Chenghao Lyu, Nuo Lei, Chaoyi Chen, Hao Zhang

“…Specifically, it achieves a 5.3% improvement in fuel economy, a 7.4% mitigation in battery SOH degradation, and a 1.7% reduction in system manufacturing cost compared to standard NSGA-III-based optimization.…”
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