Dual-Resource Scheduling with Improved Forensic-Based Investigation Algorithm in Smart Manufacturing by Yuhang Zeng, Ping Lou, Jianmin Hu, Chuannian Fan, Quan Liu, Jiwei Hu

“…In the first stage, an improved multi-objective FBI algorithm is used to obtain the Pareto front solutions of this model, in which a hybrid real and integer encoding–decoding method is used for exploring the solution space and a fast non-dominated sorting method for improving efficiency. …”
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Review of optimization modeling and solution of long-distance natural gas pipeline network by Peng ZHOU, Qi WEI

“…The optimization of the natural gas pipeline network is of great significance to reduce the operating cost of the pipeline network and improve the reliability of the natural gas supply. …”
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Optimal Distributed Dispatch of Smart Multi-Agent Energy Hubs Based on Consensus Algorithm Considering Lossy Communication Network and Uncertainty by Abdelfattah A. Eladl, Magda I. El-Afifi, Magdi M. El-Saadawi, Bishoy E. Sedhom

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Optimizing Equivalent Property-Damage-Only (EPDO) Prediction Models with Genetic Algorithms: A Case Study on Roundabout Geometric Characteristics by Hossein Samadi, Omid Rahmani, Khaled Shaaban, Amir Saman Abdollahzadeh Nasiri, Mehrzad Hasanvand

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Volt/VAr Regulation of the West Mediterranean Regional Electrical Grids Using SVC/STATCOM Devices With Neural Network Algorithms by H. Feza Carlak, Ergin Kayar

“…The modeled power system is optimized for the size and location of the FACTS devices by applying genetic algorithms (GAs) and particle swarm optimization (PSO) algorithms to the selected busbars of the FACTS devices, a strategy designed to significantly reduce system losses. …”
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Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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The Optimal Cost Design of Reinforced Concrete Beams Using an Artificial Neural Network—The Effectiveness of Cost-Optimized Training Data by Jaemin So, Seungjae Lee, Jonghyeok Seong, Donwoo Lee

“…This study presents a method for the automated design of reinforced concrete (RC) beam cross-sections using an artificial neural network (ANN) trained with cost-optimized data generated by the crow search algorithm (CSA). …”
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A Model Predictive Control to Improve Grid Resilience by Joseph Young, David G. Wilson, Wayne Weaver, Rush D. Robinett

“…Previous work on MPCs has focused on narrowly targeted control applications such as improving electric vehicle (EV) charging infrastructure or reducing the cost of integrating Energy Storage Systems (ESSs) into the grid. …”
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Multi-objective programming method for ship weather routing based on fusion of A* and NSGA-II by Yuankui LI, Jiyuan SUO, Dongye YU, Xinyu ZHANG, Fang YANG, Xuefeng YANG

“…ConclusionIn summary, the proposed method can be applied to optimize ship ocean routes under multiple constraint conditions and identify routes that meet the voyage objectives, thereby reducing operational costs, improving shipping efficiency and providing support for ship meteorological navigation and future intelligent ship navigation.…”
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Based on improved crayfish optimization algorithm cooperative optimal scheduling of multi-microgrid system by Dongmei Yan, Hongkun Wang, Yujie Gao, Shiji Tian, Hong Zhang

“…Subsequently, based on the four improvement methods of Chaotic Map, Quantum Behavior, Gaussian Distribution, and Nonlinear Control Strategy, the Chaotic Gaussian Quantum Crayfish Optimization Algorithm is proposed to solve the optimization scheduling model. …”
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Machine Learning Performance Analysis for Bagging System Improvement: Key Factors, Model Optimization, and Loss Reduction in the Fertilizer Industry by Ari Primantara, Udisubakti Ciptomulyono, Berlian Al Kindhi

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Developing an Optimization Model for Minimizing Solid Waste Collection Costs by Muciz Özcan, Semih Cengiz, Mehmet Şen

“…The Simulated Annealing (SA) algorithm, one of the heuristic optimization techniques used to identify the best solutions to complicated problems, is employed to solve the routing problem of solid waste collection vehicles in this study. …”
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Home Load Optimization Scheduling Strategy Based on Improved Binary Particle Swarm Optimization Algorithm by Li ZHANG, Qinglei LIU, Hongwei ZHANG

“…Firstly, the household loads are classified and a scheduling model is established with the objectives of lowest electricity cost, smallest carbon emission and largest comfort; secondly, based on the real-time photovoltaic output and peak-valley time-of-use electricity price, a scheduling strategy is proposed to meet the household load electricity demand through controlling the charging and discharging of energy storage; finally, the proposed model is simulated and solved using the scenario analysis method and hierarchical multi-strategy learning improved binary particle swarm optimization algorithm (HLSBPSO). …”
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Optimization Operation of the Park-Level Integrated Energy System Based on the Improved Coyote Optimization Algorithm by Jiyong Li, Yasai Wang, Yifei Zheng, Chengye Liu, Xiaoshuai Xu, Ran Chen

“…Furthermore, a distributed algorithm is proposed to resolve the game model by combining an improved coyote optimization algorithm with quadratic programming. …”
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Improved Tuna Swarm Optimization (ITSO) Algorithm based on Adaptive Fitness-Weight for Global Optimization by A. F. Seini Yussif, T. Seini, C. Adu

“… In this paper, an improved variant of the Tuna Swarm Optimization (TSO) algorithm called the Improved Tuna Swarm Optimization (ITSO) algorithm is proposed. …”
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A Multi-Strategy Improved Horned Lizard Optimization Algorithm and Its Application in Engineering Optimization by Yancang Li, Jinfan Zhang, Zidong Jin, Weitao Qiao

“…In this study, a multi-strategy improved horned lizard optimization algorithm (MSHLOA) is proposed to overcome the limitations of the standard HLOA in terms of premature convergence and slow optimization search. …”
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An Improved Coral Reef Optimization-Based Scheduling Algorithm for Cloud Computing by Shuzhen Wan, Lixin Qi

“…In this paper, we establish a resource allocation framework and propose a novel task scheduling algorithm. An improved coral reef optimization (ICRO) is proposed to deal with this task scheduling problem. …”
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Text classification using SVD, BERT, and GRU optimized by improved Seagull optimization (ISO) algorithm by Yuanyuan Chen, Nan Sun, Yuanbang Li, Rong Peng, Abbas Habibi

“…In the present research, a Gated Recurrent Unit (GRU) optimized by the Improved Seagull Optimization (ISO) algorithm was utilized to address these issues, resulting in notable improvements in classification performance. …”
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NUMERICAL CONTROL MILLING PARAMETER OPTIMIZATION ON THE BASIS OF IMPROVED GENETIC ALGORITHM by YAN ShengLi, FU Hui, LI Hao

“…Then, the ENDE-NSGA-II method is adopted to complete the parameter optimization. By adoption of the NDX crossover algorithm, CA sorting method and DE strategy can increase the search interval, ensure the population diversification distribution, and improve the convergence rate. …”
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A non-dominated sorting based multi-objective neural network algorithm of ethylene glycol hydrogenation reactor in energy reduction by Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Muhamad Nazri Murat, Ashraf Azmi

“…Abstract Artificial intelligence has revolutionized various industries, including chemical process optimization. Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overall process optimization. …”
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