Comparative Review of Multi-Objective Optimization Algorithms for Design and Safety Optimization in Electric Vehicles by I Gede S. S. Dharma, Rachman Setiawan

“…Despite the widespread use of established optimization algorithms like Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), Non-Dominated Sorting Genetic Algorithm-III (NSGA-III), and Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) in real-world engineering optimization problems, newer algorithms such as Two-Stage NSGA-II (TS-NSGA-II), Dynamic Constrained NSGA-III (DCNSGA-III), MOEA/D with Virtual Objective Vectors (MOEA/D-VOV), Large-Scale Evolutionary Multi-Objective Optimization Assisted by Directed Sampling (LMOEA-DS), and Super-Large-Scale Multi-Objective Evolutionary Algorithm (SLMEA) remain underexplored in the context of Battery Electric Vehicle (BEV) safety, particularly in optimizing complex, non-linear, and constrained multi-objective problems like crashworthiness and thermal management. …”
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Diesel Engine Urea Injection Optimization Based on the Crested Porcupine Optimizer and Genetic Algorithm by Xu Chen, Changhai Ma, Quanli Dou, Shuzhan Bai, Ke Sun, Zhenguo Li

“…Finally, the Nondominated Sorting Genetic Algorithm II (NSGA-II) was used to optimize the urea injection volume for all conditions. …”
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RRT-Based Optimizer: A Novel Metaheuristic Algorithm Based on Rapidly-Exploring Random Trees Algorithm by Guang-Jin Lai, Tao Li, Bao-Jun Shi

“…Real-world optimization problems are becoming increasingly complex and require effective and versatile algorithms to provide reliable solutions. …”
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An optimal L∞-PLA algorithm for trajectory data compression by ZHAO Huanyu, SUN Guohao, LI Tongliang, YANG Jian, PANG Chaoyi

“…MDisPLA used a divide-and-conquer strategy to extend the one-dimensional optimal PLA algorithm for optimizing compression of multi-dimensional trajectory data. …”
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Multi-strategy collaborative optimization of gravitational search algorithm by Zhonghua Yang, Yuanli Cai, Ge Li, Peng Wang, Yu Chen

“…In the early iterations, particle positions are primarily updated using the original gravitational force, preserving the inherent characteristics of the gravitational search algorithm. In the later stages, particles with better fitness values are updated using a globally optimal Lévy random walk strategy to enhance local search capabilities, while particles with poorer fitness values are updated using the sparrow algorithm follower strategy. …”
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Fast autoscaling algorithm for cost optimization of container clusters by José María López, Joaquín Entrialgo, Manuel García, Javier García, José Luis Díaz, Rubén Usamentiaga

“…In comparison to the heuristics, FCMA achieves similar solving times while consistently delivering more cost-effective solutions.…”
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Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering by V. I. Koshelev, Ngoc Hieu Trinh

“…An MDF synthesis was carried out using optimization procedures, and the effectiveness of the algorithms was assessed using computer calculations.Results. …”
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Evolving the Whale Optimization Algorithm: The Development and Analysis of MISWOA by Chunfang Li, Yuqi Yao, Mingyi Jiang, Xinming Zhang, Linsen Song, Yiwen Zhang, Baoyan Zhao, Jingru Liu, Zhenglei Yu, Xinyang Du, Shouxin Ruan

“…This paper introduces an enhanced Whale Optimization Algorithm, named the Multi-Swarm Improved Spiral Whale Optimization Algorithm (MISWOA), designed to address the shortcomings of the traditional Whale Optimization Algorithm (WOA) in terms of global search capability and convergence velocity. …”
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Application of improved particle swarm optimization algorithm combined with genetic algorithm in shear wall design by Wei Gao

“…The example results show that when using the designed shear wall design program for scheme design, the success rate reaches 100 %, which is 38.47 % higher than the original particle swarm optimization algorithm. The obtained optimization scheme has interlayer displacement angles of 1/2096 and 1/1800 in the vertical and horizontal directions, respectively, while the torsional displacement ratio in both directions is 1.0908 and the torsional period ratio is 0.7125. …”
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A novel robust multi-objective evolutionary optimization algorithm based on surviving rate by Wenxiang Jiang, Kai Gao, Shuwei Zhu, Lihong Xu

“…Despite the success of multi-objective evolutionary optimization algorithms in addressing complex optimization problems, research focusing on input disturbances remains limited. …”
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Colonial bacterial memetic algorithm and its application on a darts playing robot by Szilárd Kovács, Csaba Budai, János Botzheim

“…Abstract In this paper, we present the Colonial Bacterial Memetic Algorithm (CBMA), an advanced evolutionary optimization approach for robotic applications. …”
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Rethinking Metaheuristics: Unveiling the Myth of “Novelty” in Metaheuristic Algorithms by Chia-Hung Wang, Kun Hu, Xiaojing Wu, Yufeng Ou

“…While nature-inspired optimization methods show promise for various applications, their effectiveness is often limited by metaphor-driven design, structural biases, and a lack of sufficient theoretical foundation. …”
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APPLICATION OF QUADRATIC PROGRAMMING ON PORTFOLIO OPTIMIZATION USING WOLFE’S METHOD AND PARTICLE SWARM OPTIMIZATION ALGORITHM by Syaripuddin Syaripuddin, Fidia Deny Tisna Amijaya, Wasono Wasono, Shanaz Tulzahrah, Rara Suciati

“…In this research, the classical method uses Wolfe’s method, while the heuristic method uses the particle swarm optimization (PSO) algorithm. …”
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Multi strategy Horned Lizard Optimization Algorithm for complex optimization and advanced feature selection problems by Marwa M. Emam, Mosa E. Hosney, Reham R. Mostafa, Essam H. Houssein

“…The Horned Lizard Optimization Algorithm (HLOA) is a nature-inspired metaheuristic that mathematically mimics the adaptive defense mechanisms of horned lizards, including crypsis, skin color modulation, blood-squirting, and escape movements. …”
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Well Pattern optimization as a planning process using a novel developed optimization algorithm by Seyed Hayan Zaheri, Mahdi Hosseini, Mohammad Fathinasab

“…The results indicate that while the genetic algorithm and particle swarm optimization do not guarantee optimal outcomes, the newly developed algorithm outperforms both methods. …”
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Appraising the Pile Settlement Rates by Support Vector Regression Optimized Using the Novel Optimization Algorithms by Argyros Maris

“…Biogeography-Based Optimization (BBO) and Flow Direction Algorithm (FDA) were coupled with SVR to create the SVR-FDA and SVR-BBO frameworks. …”
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Renewable energy forecasting using optimized quantum temporal model based on Ninja optimization algorithm by Mona Ahmed Yassen, El-Sayed M. El-kenawy, Mohamed Gamal Abdel-Fattah, Islam Ismael, Hossam El.Deen Salah Mostafa

“…Experimental implementation revealed that incorporating the Ninja Optimization Algorithm with the QTM model delivered the best R2 performance at 95.15% with an exceptional RMSE value of 0.00003, thus establishing its ability to optimize renewable energy forecasting accuracy.…”
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Low-carbon economic optimization for flexible DC distribution networks based on the hiking optimization algorithm by Ke Wu, Yuefa Guo, Ke Wang, Zhenliang Chen

“…The proposed model is solved using a novel Hiking Optimization Algorithm (HOA), and comparative analysis across different scenarios is conducted to investigate the impact of the carbon trading strategy on low-carbon operation, alongside an evaluation of the system’s economic and environmental performance under reasonable scheduling of both the carbon trading strategy and flexible loads. …”
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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

“…Statistical analyses including the Wilcoxon rank sum test (p < 0.05), Friedman’s test, and solution distribution visualization validate the robustness of the algorithm against local optimal stagnation. In the engineering optimization example, the average cost of the pressure vessel problem was reduced by 55.6%, while the optimal value with the lowest standard deviation verified its stability in terms of solution accuracy, convergence speed, and stability. …”
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Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms by Yuhong MA, Wen PANG, Daqi ZHU

“…Simulation results demonstrate that the proposed algorithm reduces the average path length by 15.4% and 7.5% compared to traditional genetic algorithm and particle swarm optimization, respectively, while improving computational efficiency by 45.5% and 16.8%.…”
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