A Class of Efficient Algorithms for the Bi-Level Demand Adjustment Problems in Congested Traffic Networks by Lan Cheng, Jun Xie, Jun Huang, Liyang Feng, Qianni Wang, Hongtai Yang

“…This paper studies a class of gradient-descent heuristic algorithms for the bi-level demand adjustment problem (DAP), which seeks to adjust origin-destination (OD) matrices based on observed link flows in congested transportation networks. …”
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A Two-Stage Greedy Genetic Algorithm for Simultaneous Delivery and Monitoring Tasks with Time Windows by Mingyang Tang, Jiaying Sun, Rongyang Zou

“…The simulation results indicate that TGGA outperforms existing heuristic algorithms.…”
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Node Selection Algorithms with Data Accuracy Guarantee in Service-Oriented Wireless Sensor Networks by Hongju Cheng, Ronglie Guo, Yuzhong Chen

“…Secondarily, we have proposed two heuristic algorithms, namely, Separate Selection Algorithm (SSA) and Combined Selection Algorithm (CSA). …”
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Parameter Selection for PSO-Based Hybrid Algorithms and Its Effect on Crack Detection in Cantilever Beams by Amin Ghannadiasl, Saeedeh Ghaemifard

“…The importance of the parameters of any optimization algorithm, especially meta-heuristic algorithms that have been created to simplify the solution of optimization problems, is inevitable. …”
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A novel intelligent photonic design method enabled by metamaterials and k-nearest neighbor by Fan Hangming, Pan Junlin, Wang Yongchen, Yuan Zhe, Cheng Mengfan, Yang Qi, Liu Deming, Deng Lei

“…Here, we present an efficient methodology that combines metamaterials, heuristic algorithms, and machine learning to facilitate the rapid development of intricate devices. …”
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Optimal Design of a Hazardous Materials Transportation Network considering Uncertainty in Accident Consequences by Hongfei Jia, Junzhe Li

“…The model is transformed using chance-constrained programming and solved using heuristic algorithms. We apply the model to the highway network in Anhui province, China, to verify its validity. …”
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Different Meta-Heuristic Optimized Radial Basis Function Neural Network Models for Short-Term Power Consumption Forecasting by Dhivagar Shanmugam, V Ramana

“…Specifically, the coefficient of determination (R²) values for the training, testing, and total datasets are 0.9994, 0.9920, and 0.9985, respectively, demonstrating that AGWO is the most precise optimizer among the studied meta-heuristic algorithms.…”
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Hybrid LSTM-PSO optimization techniques for enhancing wind power bidding efficiency in electricity markets by Viet Anh Truong, Ngoc Sang Dinh, Thanh Long Duong, Ngoc Thien Le, Cong Dinh Truong, Linh Tung Nguyen

“…Past research has predominantly focused on utilizing meta-heuristic algorithms to optimize neural network structures, while the exploration of deep learning in optimization has remained relatively limited. …”
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Design and Analysis of FOPID-Based Damping Controllers Using a Modified Grey Wolf Optimization Algorithm by Manoj Kumar Kar, Sanjay Kumar, Arun Kumar Singh, Sibarama Panigrahi, Murthy Cherukuri

“…The results obtained from the MGWOA-tuned FOPID-based damping controllers are compared with those obtained using recently developed efficient and competitive heuristic algorithms. It was observed that the MGWOA method is well-suited for damping low-frequency oscillations. …”
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A Bayesian Neural Network-Based Method to Calibrate Microscopic Traffic Simulators by Qinqin Chen, Anning Ni, Chunqin Zhang, Jinghui Wang, Guangnian Xiao, Cenxin Yu

“…Based on the BNN model with the best performance, heuristic algorithms (HAs) are performed to seek the optimal values of the parameters to be calibrated with the minimum difference between the predicted results of BNN and the field-measured values. …”
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Millimeter-Wave Underlay D2D Communications: Channel Assignment, Transmission mode Selection and Power Control for Full-CSI and Limited-CSI Scenarios by Nima Reisi

“…As the optimization problem is mixed-integer-non-linear programming, two heuristic algorithms are proposed, assuming full Channel Side Information (CSI) and limited CSI at Base Station, respectively. …”
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Adaptive Gradient-Based Optimization Method for Parameter Identification in Power Distribution Network by Bin Li, Yehai Jiang, Ke Hu, Xiangyi Zhou, Haoran Chen, Shihe Xu, Hao Jiao, Jinming Chen

“…By comparing the proposed method and several heuristic algorithms, it is found that the errors in both three criteria via our solution are much lower with a much smoother and more stable convergence of loss function. …”
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Current development and future prospects of multi-target assignment problem: A bibliometric analysis review by Shuangxi Liu, Zehuai Lin, Wei Huang, Binbin Yan

“…Subsequently, existing solution algorithms for the MTA problem are reviewed, generally falling into three categories: exact algorithms, heuristic algorithms, and machine learning algorithms. Finally, a development framework is proposed based on the ''HIGH'' model (high-speed, integrated, great, harmonious) to guide future research and intelligent weapon system development concerning the MTA problem. …”
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Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time by Hongwei Li, Yuvraj Gajpal, Chirag Surti, Dongliang Cai, Amit Kumar Bhardwaj

“…This paper provides mathematical models, heuristic algorithms, and two nature-based metaheuristic algorithms to solve the problem. …”
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Estimation of Ultimate Bearing Capacity in Rock-Socketed Piles Using Optimized Machine Learning Approaches by Ali Hassan, Hamza Rashid

“…To enhance the model's precision, the study incorporates two state-of-the-art meta-heuristic algorithms, the Artificial Hummingbird Algorithm (AHA) and the Improved Grey Wolf Optimizer (IGWO), into the analysis. …”
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Self-Administered Information Sharing Framework Using Bioinspired Mechanisms by Huibo Bi, Yanyan Chen, Wen-Long Shang, Chengcheng Song, Wenbo Huang

“…Previous research mainly focuses on investigating novel protocols to save energy by reducing data traffic with the aid of optimal or heuristic algorithms. However, data packet behaviours and significant parameters involved are mostly preconfigured in a supervised-learning fashion rather than using an unsupervised learning paradigm and therefore may not adapt to uncertain or fast-changing environments. …”
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Inverse design of nanophotonic devices enabled by optimization algorithms and deep learning: recent achievements and future prospects by Kim Junhyeong, Kim Jae-Yong, Kim Jungmin, Hyeong Yun, Neseli Berkay, You Jong-Bum, Shim Joonsup, Shin Jonghwa, Park Hyo-Hoon, Kurt Hamza

“…We discuss representative methods commonly employed in nanophotonic design, including various meta-heuristic algorithms such as trajectory-based, evolutionary, and swarm-based approaches, in addition to adjoint-based optimization. …”
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Reliability-Based Optimum Design of Dome Truss Structures through Enhanced Vibration Particle System by Pedram Hosseini, Nasibeh Hatami, Seyed Rohollah Hoseini Vaez

“…Also, reliability index 3 is set as the minimum target reliability index. Meta-heuristic algorithms can be used to achieve optimal design and appropriate safety since mathematical calculations are time-consuming. …”
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Soft computing paradigm for climate change adaptation and mitigation in Iran, Pakistan, and Turkey: A systematic review by Muhammad Talha, A. Pouyan Nejadhashemi, Kieron Moller

“…Although some articles utilized multiple techniques, classical ML methods appeared in approximately 37.3 % of the studies, neural network paradigms in about 57.5 %, and optimization or meta-heuristic algorithms in around 5.0 %. Regarding thematic focus, about 33.3 % of the articles addressed water resource management, 22.2 % focused on climate prediction, 11.1 % on land and agriculture, 9 % on ecosystem modeling, and 24.2 % on natural disaster preparedness and response. …”
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Multiobjective Salp Swarm Algorithm Approach for Transmission Congestion Management by Anjali Agrawal, Seema N. Pandey, Laxmi Srivastava, Pratima Walde, R. K. Saket, Baseem Khan

“…To examine the proposed approach, it has been implemented on IEEE 30-bus system and a bigger power system IEEE 118-bus system; as well as the proposed technique of MOSSA has been compared and found better than reported methods and two other meta heuristic algorithms (multiobjective modified sperm swarm optimization and multiobjective adoptive rat swarm optimization).…”
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