Algorithms for Non-Relativistic Quantum Integral Equation by Jorge Henrique de Oliveira Sales, Pedro Henrique Sales Girotto

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Parrett's type models in simulated annealing algorithms by Gražvydas Felinskas, Leonidas Sakalauskas

“… In this paper a simulated annealing algorithm for continuous global optimization is considered. …”
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Algorithms for Searching the Shortest Path and Its Modification by N. I. Listopad, I. A. Karuk, A. A. Hayder

“…The modified algorithm and its UML diagram are presented.…”
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Special Issue: “Optimization Algorithms: Theory and Applications” by Frank Werner

“…This Special Issue of the journal <i>Mathematics</i> was dedicated to compiling new results in the area of optimization algorithms, and both theoretical works and practical applications have been searched [...]…”
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Classical and quantum algorithms for many-body problems by Ayral, Thomas

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Implementations of Signal-Processing Algorithms for OFDM Systems by Ming-Der Shieh, Yin-Tsung Hwang, Hanho Lee, Chirn Chye Boon, Zhiyuan Yan

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Hybrid Algorithms of Nonexpansive Semigroups for Variational Inequalities by Peixia Yang, Yonghong Yao, Yeong-Cheng Liou, Rudong Chen

“…Two hybrid algorithms for the variational inequalities over the common fixed points set of nonexpansive semigroups are presented. …”
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Research on the scalability of parallel community detection algorithms by Qiang LIU, Yan JIA, Binxing FANG, Bin ZHOU, Yue HU, Jiuming HUANG

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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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WSN clustering routing algorithm based on Cuckoo Search algorithm optimized K-means by Kailei ZHU, Aijing SUN

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Optimized coverage algorithm of wireless video sensor network based on quantum genetic algorithm by Fu-you FAN, Guo-wu YANG, Qian-qi LE, Feng-mao LV, Chao ZHAO

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Enhancing Algorithmic Literacy: Experimental Study on Communication Students’ Awareness of Algorithm-Driven News by Jose Manuel Noguera-Vivo, María del Mar Grandío-Pérez

Subjects: “…algorithmic literacy…”
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Parallel association rules incremental mining algorithm based on information entropy and genetic algorithm by Yimin MAO, Qianhu DENG, Zhigang CHEN

“…Aiming at the problems that in the big data environment, the Can-tree based incremental association rule algorithm had problems such as too much space occupation of the tree structure, inability to dynamically set the support threshold, and too much time consumption during the data transfer process between the Map and Reduce stages, the Map Reduce-based parallel association rules incremental mining algorithm using information entropy and genetic algorithm (MR-PARIMIEG)was proposed.Firstly, a similar items merging based on information entropy (SIM-IE) was designed to merge similar data items, and a Can tree based on the merged data set was constructed, thereby reducing the space occupation of the tree structure.Secondly, the dynamic support threshold obtaining using genetic algorithm (DST-GA) was proposed to obtain the relatively optimal dynamic support threshold in the big data environment, and frequent itemset mining was performed according to this threshold to avoid the unnecessary time consumption caused by mining redundant frequent patterns.Finally, in the process of MapReduce parallel operation, the parallel LZO data compression algorithm was used to compress the output data of the Map stage, thereby reducing the size of the transmitted data, and finally improving the running speed of the algorithm.Experimental simulation results show that MR-PARIMIEG has better performance when mining frequent item sets in the big data environment, and it is suitable for parallel processing of larger data sets.…”
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Improved particle filter algorithm combined with culture algorithm for collision Caenorhabditis elegans tracking by Taoyuan Yu, Xiping Xu, Yuanpeng Li, Ning Zhang, Naiyu Zhang, Xiaohui Wang

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Improved ant colony algorithm based cloud computing user task scheduling algorithm by Sining LUO, Hualong WANG, Hongyu LI, Wei PENG

“…In recent years,with the development of power information,more and more power applications and tasks are deployed in the cloud.Because of the dynamic heterogeneity of cloud resources and power applications,it is a challenge in the cloud computing system to realize resource division and task scheduling.Power applications need to be able to achieve a rapid response and minimum completion time,and schedulers should consider the load of each cloud computing node to ensure the reliability of cloud computing.A task scheduling algorithm based on the algorithm of improving an ant colony was proposed to solve the problem of task scheduling in virtual machines.Through the improvement of the standard ant colony algorithm,the task scheduling time was reduced and load balancing was realized while minimizing the overall completion time.The results show that the algorithm can shorten the task scheduling time and realize the load balancing of cloud nodes,which provides technical basis for the optimization of power cloud computing.…”
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Retracted: Improvement and Optimization of Feature Selection Algorithm in Swarm Intelligence Algorithm Based on Complexity by null Complexity

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Multi-duplication fault tolerant scheduling algorithm based on genetic algorithm in heterogeneous systems by Zhong-zheng HE, Chao-guang MEN, Yong-jun CHEN, Xiang LI

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A Comparative Study on Solving Optimization Problems With Exponentially Fewer Qubits by David Winderl, Nicola Franco, Jeanette Miriam Lorenz

Subjects: “…Hybrid algorithms…”
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Comparison of Unsupervised Learning Algorithms for Clustering Cuban Citizens using a Lifestyle Questionnaire by S. Torres, D. Alonso, N. Martinez, S. Merced

Subjects: “…algorithms…”
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Book Review by Shiva Singh

Subjects: “…Algorithms…”
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