A new multi objective crested porcupines optimization algorithm for solving optimization problems by Divya Adalja, Pinank Patel, Nikunj Mashru, Pradeep Jangir, Arpita, Reena Jangid, G. Gulothungan, Mohammad Khishe

“…MOCPO performance is compared with state-of-the-art algorithms like the Multi-Objective Gradient Based Optimizer (MOGBO), Preference inspired Differential Evolution (Pre-DEMO), Multi-Objective Exponential Distribution Algorithm (MOEDO), Pivot solution based Multi-Objective Evolutionary Algorithm (Pi-MOEA), and Clustering aided Grid based Multi-Objective Evolutionary Algorithm (ClGrMOEA). …”
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Comprehensive influence evaluation algorithm of complex network nodes based on global-local attributes by Weijin JIANG, Ying YANG, Tiantian LUO, Wenying ZHOU, En LI, Xiaowei ZHANG

“…Mining key nodes in the network plays a great role in the evolution of information dissemination, virus marketing, and public opinion control, etc.The identification of key nodes can effectively help to control network attacks, detect financial risks, suppress the spread of viruses diseases and rumors, and prevent terrorist attacks.In order to break through the limitations of existing node influence assessment methods with high algorithmic complexity and low accuracy, as well as one-sided perspective of assessing the intrinsic action mechanism of evaluation metrics, a comprehensive influence (CI) assessment algorithm for identifying critical nodes was proposed, which simultaneously processes the local and global topology of the network to perform node importance.The global attributes in the algorithm consider the information entropy of neighboring nodes and the shortest distance nodes between nodes to represent the local attributes of nodes, and the weight ratio of global and local attributes was adjusted by a parameter.By using the SIR (susceptible infected recovered) model and Kendall correlation coefficient as evaluation criteria, experimental analysis on real-world networks of different scales shows that the proposed method is superior to some well-known heuristic algorithms such as betweenness centrality (BC), closeness centrality (CC), gravity index centrality(GIC), and global structure model (GSM), and has better ranking monotonicity, more stable metric results, more adaptable to network topologies, and is applicable to most of the real networks with different structure of real networks.…”
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Evolution of deep learning tooth segmentation from CT/CBCT images: a systematic review and meta-analysis by Wai Ying Kot, Sum Yin Au Yeung, Yin Yan Leung, Pui Hang Leung, Wei-fa Yang

“…Conclusions Multiple deep learning algorithms have been successfully applied to tooth segmentation from CT/CBCT and their evolution has been well summarized and categorized according to their backbone structures. …”
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A Multipopulation Firefly Algorithm for Correlated Data Routing in Underwater Wireless Sensor Networks by Ming Xu, Guangzhong Liu

“…We design three kinds of fireflies and their coordination rules in order to improve the adaptability of building, selecting, and optimization of routing path considering the data correlation and their sampling rate in various sensor nodes. Different groups of fireflies conduct their optimization in the evolution in order to improve the convergence speed and solution precision of the algorithm. …”
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A Constrained Multi-Objective Optimization Algorithm with a Population State Discrimination Model by Shaoyu Zhao, Heming Jia, Yongchao Li, Qian Shi

“…Tailored environmental selection models are then designed for the auxiliary population according to different states, enabling them to guide the evolution of the main population more effectively. …”
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PSLDV-Hop: a robust localization algorithm for WSN using PSO and refinement process by Bhupinder Kaur, Deepak Prashar, Arfat Ahmad Khan, Seifedine Kadry, Jungeun Kim

“…By utilizing an improved iterative evolution algorithm, the PSLDV-Hop algorithm reduces localization errors by achieving a higher degree of accuracy in node localization. …”
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A similarity-based multi-objective test optimization technique using search algorithm by Amir Sohail Habib, Saif Ur Rehman Khan, Shahid Hussain, Naseem Ibrahim, Habib un Nisa, Abdullah Yousafzai

“…Inspired by this, we propose a Similarity-based Multi-Objective Optimization Technique (SMOOT) for test suite reduction using a Grey Wolf Optimizer (GWO) algorithm. The proposed technique employs different similarity metrics, including Cosine Similarity, Euclidean Distance, Jaccard Similarity, Manhattan Distance, and Minkowski Distance, to evaluate the similarity score of the tests. …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…ObjectiveThe movement of sediment particles significantly affects riverbed evolution, establishing it as a central concern and ongoing challenge in fluvial dynamics research. …”
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Intraspecific Differentiation of <i>Francisella tularensis</i> Strains Using Multilocus Real-Time Polymerase Chain Reaction by N. A. Osina, D. A. Sitmbetov, E. G. Bulgakova, S. S. Chekmareva, E. V. Sazanova, A. M. Senichkina, O. Yu. Lyashova, A. V. Osin, S. A. Shcherbakova

“…Sequence homology was assessed using the BLAST algorithm and the GenBank NCBI database. Results and discussion. …”
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Quality of Service Routing in Manet Using a Hybrid Intelligent Algorithm Inspired by Cuckoo Search by S. Rajalakshmi, R. Maguteeswaran

“…This updating mechanism is derived from the differential evolution (DE) algorithm, where the candidates learn from diversified search regions. …”
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M-Race: A Racing Algorithm for the Tuning of Meta-Heuristics Based on Multiple Performance Objectives by Christoff Jordaan, Andries Engelbrecht, Kian Anderson

“…Experimental results demonstrate that M-race successfully discovered between 9 and 15 non-dominated parameter configurations across benchmark functions for both particle swarm optimisation (PSO) and differential evolution (DE) algorithms. These non-dominated parameter configurations represent balances among the tuning objectives used.…”
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Dye-cleaning prediction with a variant of nature-inspired algorithms coupled with extreme gradient boosting by Tiyasha Tiyasha, Chijioke Elijah Onu, Mohamed A. Ismail, Rama Rao Karri, Abdelfattah Amari, Vinay Kumar, Suraj Kumar Bhagat

“…Hyperparameter tuning via differential evolution (DE), genetic algorithm (GA), random search (RS), and grid search (GS) with the XGBoost model was conducted to achieve more accurate results. …”
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Social Cognitive Optimization Algorithm for Approximate Path Generation Synthesis of Spherical 4R Linkage by Che Linxian, Huang Yonggang, Du Li

“…Combining the self-adaptive penalty function method，this study employs the social cognitive optimization (SCO) algorithm to solve the aforementioned problem. In order to enhance the convergence speed and accuracy of SCO algorithm，a novel accelerating social cognitive optimization (ASCO) algorithm is proposed in which the differential evolution (DE) operators are used to local search. …”
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Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath Clustering by Yupeng Li, Jianhua Zhang, Ruisi He, Lei Tian, Hewen Wei

“…To address this issue, a hybrid differential evolution (DE) and EM (DE-EM) algorithms are proposed in this paper. …”
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Structure design and trajectory positioning method of underwater telescopic arm robot based on DE algorithm by Jin Huawei, Li Shuo, Liu Wenjian, Ji Haitao, Yan Fangzheng, Lu Wenlong, Xu Chenyu

“…Considering the possible collision in the trajectory of the underwater robot arm and the increase in load pressure on the arm, the differential evolution method is introduced to iterate the time of the arm through six stages to plan the optimal value of time for the optimal trajectory of the arm, and finally, the algorithm is applied to the experiment. …”
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The optimization of low Earth orbit satellite constellation visibility with genetic algorithm for improved navigation potential by Chao Qin, Yanbin Gao, Yihuan Wang

“…Overall, the proposed GA outperformed Particle Swarm Optimization and Dynamic Non-dominated Sorting Differential Evolution in visibility, robustness, and computational efficiency. …”
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New Maps of Lunar Surface Oxide Abundances and Mg# Using an Optimized Ensemble Learning Algorithm by Chaofa Bian, Kefei Zhang, Yunzhao Wu, Suqin Wu, Yu Lu, Yabo Duan, Huajing Wu, Zhenxing Zhao, Wei Wu

“…The oxide and Mg# distributions in three craters from different geological units&#x2014;Highlands, SPA basin, and Maria&#x2014;indicate different magmatic evolution processes, providing new insights into lunar geological evolution and volcanism.…”
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An adapted Black Widow Optimization Algorithm for Financial Portfolio Optimization Problem with cardinalty and budget constraints by Rahenda Khodier, Ahmed Radi, Basel Ayman, Mohamed Gheith

“…New features are introduced for the BWAPO to adapt better to the problem, including (1) mating attraction and (2) differential evolution mutation strategy. The proposed BWAPO is evaluated against other metaheuristic approaches used in portfolio optimization from literature, and its performance demonstrates its effectiveness through comparative studies on benchmark datasets using multiple performance metrics, particularly in the unconstrained Mean-Variance portfolio optimization version. …”
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A Trajectory Data-Driven Study on the Evolution Mechanism and Control Strategies of Lane-Changing Behavior in Intersection Areas of Expressways by Jiayou Wu, Yongwei Lei, Shaoliu Liu, Qiang Luo

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Multi-objective particle swarm optimization algorithm for task allocation and archived guided mutation strategies by Jianjie Chen, Yanmin Liu, Yi Luo, Aijia Ouyang, Jie Yang, Wuer Bai

“…Abstract In this paper, we propose a novel multi-objective particle swarm optimization algorithm with a task allocation and archive-guided mutation strategy (TAMOPSO), which effectively solves the problem of inefficient search in traditional algorithms by assigning different evolutionary tasks to particles with different characteristics. …”
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