A hybrid differential evolution particle swarm optimization algorithm based on dynamic strategies by Huarong Xu, Qianwei Deng, Zhiyu Zhang, Shengke Lin

“…Abstract Particle Swarm Optimization (PSO), a meta-heuristic algorithm inspired by swarm intelligence, is widely applied to various optimization problems due to its simplicity, ease of implementation, and fast convergence. …”
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Application of an improved pelican optimization algorithm based on comprehensive strategy in PV parameter identification by Xu Yong, Sang Bicong, Zhang Yi

“…Secondly, the position update formula of the Pelican optimization algorithm in the global detection phase is replaced by the position update formula of the red-tailed Eagle optimization algorithm in the soaring phase to obtain the adequacy of the Pelican optimization algorithm in solution space search. …”
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Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance Optimization by Ruochen Zhang, Hyeung-Sik Choi, Dongwook Jung, Hyunjoon Cho, Phan Huy Nam Anh, Mai The Vu

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Green vehicle routing optimization based on dynamic constraint selection co-evolutionary algorithm by Lu-jie Zhou, Hai-fei Zhang, Jun-hao Fu

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Multi-Search Strategy-based Improved Water Flow Optimizer Algorithm for Cluster Analysis by Prateek Thakral, Yugal Kumar

“…Hence, this work presents an improved water flow optimizer (IWFO) algorithm for cluster analysis that can address the issues of traditional and heuristic algorithms. …”
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Improved Hybrid A* Algorithm Based on Lemming Optimization for Path Planning of Autonomous Vehicles by Yong Chen, Yuan Liu, Wei Xu

“…Path planning for autonomous vehicles is a core component of intelligent transportation systems, playing a key role in ensuring driving safety, improving driving efficiency, and optimizing the user experience. …”
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Pedestrian Re-Recognition Algorithm Based on Optimization Deep Learning-Sequence Memory Model by Feng-Ping An

“…Based on the above explanation, this paper proposes a pedestrian re-recognition algorithm based on an optimized LSTM deep learning-sequence memory learning model. …”
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Scalable bearing fault diagnosis using metaheuristic feature selection and machine learning for diverse operating conditions by B. R. Nayana, R. Subha, Rekha Radhakrishnan, P. Geethanjali

“…Bearings are the foremost component of machinery that fails; hence early diagnosing mechanisms aided by artificial intelligence techniques play a crucial role. The objective of this study is to develop a scalable model for real-time bearing fault diagnosis using recent evolutionary algorithms such as, Marine Predator Algorithm, Equilibrium Optimization, Henry Gas Solubility Optimization, and Poor and Rich Optimization for optimal Feature Selection. …”
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Application of the Multi-Strategy Improved Walrus Optimization Algorithm in Mobile Robot Path Planning by Yongfu Ke, Limei Shi, Weinan Ji, Peng Luo, Lei Guo

“…To this end, this paper proposes the Improved Walrus Optimization Algorithm (IWaOA) and applies it to path planning. …”
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Research on Reactor Radiation Shielding Optimization Method Based on Multi-objective Evolutionary Algorithm by LIU Chengwei1, 2, CHEN Zhenping1, 2, , YANG Chao1, 2, ZHANG Huajian1, 2, SUN Aikou1, 2, LEI Jichong1, 2, YU Tao1, 2

“…Traditional multi-objective optimization methods for radiation shielding suffer from limitations such as a restricted number of optimization objectives, a limited set of optimization parameters, and suboptimal global optimization, rendering them inadequate for intelligent radiation shielding design. …”

Predicting carbon dioxide emissions using deep learning and Ninja metaheuristic optimization algorithm by Anis Ben Ghorbal, Azedine Grine, Ibrahim Elbatal, Ehab M. Almetwally, Marwa M. Eid, El-Sayed M. El-Kenawy

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Sustainable soil organic carbon prediction using machine learning and the ninja optimization algorithm by Anis Ben Ghorbal, Azedine Grine, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy

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Multi-objective optimization for smart cities: a systematic review of algorithms, challenges, and future directions by YiFan Chen, Weng Howe Chan, Eileen Lee Ming Su, Qi Diao

“…With the growing complexity and interdependence of urban systems, multi-objective optimization (MOO) has become a critical tool for smart-city planning, sustainability, and real-time decision-making. …”
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Optimizing Artificial Neural Network Learning Using Improved Reinforcement Learning in Artificial Bee Colony Algorithm by Taninnuch Lamjiak, Booncharoen Sirinaovakul, Siriwan Kornthongnimit, Jumpol Polvichai, Aysha Sohail

“…To overcome this challenge, this study introduces an improved optimization approach, the improvement of reinforcement learning in the artificial bee colony (improved R-ABC) algorithm, to enhance the optimization process for ANNs. …”
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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

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Joint Active/Passive Beamforming Optimization via RWMMSE and Gradient Projection for Downlink IRS-Aided MU-MISO Systems by Seraphin F. Kimaryo, Eduard E. Bahingayi, Kyungchun Lee

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Advanced Sales Route Optimization Through Enhanced Genetic Algorithms and Real-Time Navigation Systems by Wilmer Clemente Cunuhay Cuchipe, Johnny Bajaña Zajia, Byron Oviedo, Cristian Zambrano-Vega

“…This study proposes a novel Hybrid Genetic Algorithm (GAAM-TS) that integrates Adaptive Mutation, Tabu Search, and an LSTM-based travel time prediction model to enable real-time, intelligent route planning. …”
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Multi-Population Optimization Framework Based on Plant Evolutionary Strategy and Its Application to Engineering Design Problems by Hongwei Cheng, Jun Li, Xiaoming Zhang, Tingjuan Li, Panpan Zhang

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A Hybrid Optimization Framework for Dynamic Drone Networks: Integrating Genetic Algorithms with Reinforcement Learning by Mustafa Ulaş, Anıl Sezgin, Aytuğ Boyacı

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Identifying Optimal Spatial Groups for Maximum Coverage in Ubiquitous Sensor Network by Using Clustering Algorithms by Simon Fong, Weng Fai Ip, Elaine Liu, Kyungeun Cho

“…This paper explores this problem via optimal “spatial groups” clustering. Simulation experiments by using clustering algorithms and linear programming are to be conducted, for evaluating their effectiveness comparatively.…”
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