An improved hybrid artificial bee colony algorithm for a multi-supplier closed-loop location inventory problem with customer returns. by Hao Guo, Xiaomei Lai, Ju Guo, Ge You, Ibrahim Alnafrah

“…The objective of the CLLIP is to minimize overall supply chain costs by optimizing facility location and inventory management strategies. …”
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PSO Based Optimization of Testing and Maintenance Cost in NPPs by Qiang Chou, Daochuan Ge, Ruoxing Zhang

“…In this paper, we adopt PSO as an optimizer to optimize the multiobjective optimization problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. …”
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Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements by Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen

“…This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. …”
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THE ALGORITHMIC MODEL OF LABORATORY DIAGNOSTICS OPTIMIZATION by G. I. Nazarenko, O. V. Andropova

“…Introduction of algorithmic approach is able to optimize diagnostics and its costs. …”
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Optimal Configuration of Electricity-Hydrogen Hybrid Energy Storage System Based on Multi-objective Artificial Hummingbird Algorithm by Zijing LU, Zishou LI, Xiangguo GUO, Bo YANG

“…The multi-objective artificial hummingbird algorithm based on Pareto is used to solve the planning scheme and then compared with the multi-objective particle swarm optimization and multi-objective atomic orbital search algorithm. …”
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CRASHWORTHINESS DESIGN AND OPTIMIZATION FOR COLLISION POST OF TRAIN by SHI YueQing, QIN RuiXian, CHEN BingZhi

“…In order to improve the crashworthiness of the collision post structure, the optimal cross-section configuration of the collision post was obtained based on the topology optimization method, and the impacting finite element model of the collision post was established in the explicit dynamics software Ls-Dyna. …”
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An Improved NSGA‐III With Hybrid Crossover Operator for Multi‐Objective Optimization of Complex Combined Cooling, Heating, and Power Systems by Lejie Ma, Dexuan Zou

“…The effectiveness of CCHP‐Plus is assessed using three key indicators: primary energy consumption, operational cost, and CO2 emissions. NSGAIII‐AC‐GM delivers a 20% reduction in operational costs and a 10% decrease in CO2 emissions, outperforming seven other algorithms in optimization efficiency on DTLZ and IMOP problems. …”
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Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance by Sugunakar Mamidala, Yellapragada Venkata Pavan Kumar, Rammohan Mallipeddi

“…These approaches rely on fixed models, often leading to inefficient energy use, higher operational costs, and increased traffic congestion. This paper proposes a novel framework that integrates deep Q networks (DQNs) for real-time charging optimization, coupled with multimodal bioinspired algorithms like ant lion optimization (ALO) and moth flame optimization (MFO). …”
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Comprehensive recognition algorithm of RS code based on fast code root trial by Xiaolin ZHANG, Xiuqiao LI, Rongchen SUN

“…In order to solve the problem of high computation and high missed alarm probability of RS (Reed-Solomon) codes for recognition, comprehensive recognition algorithm of RS codes based on fast code root trial was proposed.Firstly, the check relationship was solved in binary equivalently and fast code root trial was used to check parameters in sequence.Secondly, according to distribution characteristics of the combined code roots, m-level primitive polynomial field and error correction ability was associatively determined.Finally, the short codes and long codes were given different confidence weights and the determined parameters were comprehensively analyzed.The optimal parameter was selected and the generate polynomial was calculated.The proposed algorithm did not need prior information such as signal-to-noise ratio (SNR), and had good adaptability.The simulation results show that the proposed algorithm can effectively reduce the missed alarm probability under the condition of low complexity.Compared with the conventional hard decision algorithm, the performance of the proposed algorithm is improved, and the parameter recognition of RS codes can be completed quickly.…”
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Assessment of energy management and power quality improvement of hydrogen based microgrid system through novel PSO-MWWO technique by Hafiz Ghulam Murtza Qamar, Xiaoqiang Guo, Ehab Seif Ghith, Mehdi Tlija, Abubakar Siddique

“…The achieved results and numerical analysis affirm the superiority of the proposed technique compared to other traditional methods like mixed integer linear programming (MILP), HOMER, Variable mesh optimization (VMO), and Cataclysmic genetic algorithm in optimizing component sizing, renewable production, hydrogen production, reliability, cost effective, and overall efficacy. …”
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A Theoretical Bound Which Improves the Performance of Compilation-Based Multi-Agent Path Finding by Rodrigo Lopez, Roberto Asin-Acha, Jorge A. Baier

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Multi-Target Firefighting Task Planning Strategy for Multiple UAVs Under Dynamic Forest Fire Environment by Pei Zhu, Shize Jiang, Jiangao Zhang, Ziheng Xu, Zhi Sun, Quan Shao

“…Results from benchmark tests and case studies indicate that the improved MP–GWO algorithm outperforms the grey wolf optimizer (GWO), pelican optimizer (POA), Harris hawks optimizer (HHO), coyote optimizer (CPO), and particle swarm optimizer (PSO) in solving more complex optimization problems, providing better average results, greater stability, and effectively reducing flight time and path cost. …”
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Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems by Mohammad Aljaidi, Pradeep Jangir, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, Ali Fayez Alkoradees, Arpita, Aseel Smerat

“…The FATA algorithm is evaluated against recently developed and improved optimization techniques, such as rime-ice formation phenomenon based Improved RIME (IRIME) Algorithm, Newton–Raphson-Based Optimization (NRBO), Resistance Capacitance Algorithm (RCA), Krill Optimization Algorithm (KOA), and Grey Wolf Optimizer (GWO), across multiple optimization objectives: reduction in generation cost, reduction in power loss and combined generation cost plus power loss, termed as Gross cost function. …”
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Noise Processing Method of MEMS Tilt Sensor Using Improved Kalman Filter Based on Quantum Particle Swarm Optimization by Yutong Ge, Weizheng Ren, Kaile Yu, Yiran Zhang, Yuxiao Li

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Research on manufacturing quality improvement based on product gene evaluation method and a meta-heuristic algorithm with hybrid encoding scheme by Wenxiang Xu, Chao Wang, Shimin Xu, Junyong Liang, Dezheng Liu, Baigang Du

“…To address the model, an improved genetic algorithm (GA) and artificial bee colony algorithm (ABC) with hybrid encoding scheme (H-IGA-IABC) is designed by considering the different types of gene elements. …”
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Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…Additionally， the Dijkstra algorithm is improved to plan charging paths more effectively by including real-time road condition data. …”
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Low Carbon Economic Dispatch of Power System Based on Multi-Region Distributed Multi-Gradient Whale Optimization Algorithm by Linfei Yin, Yongzi Ye, Xiaoping Xiong, Jiajia Chai, Hanzhong Cui, Haoyuan Li

“…In this study, MRDMGWOA is simulated on the IEEE 39 system and 118 system, and its performance is compared with other heuristic algorithms. The results show that: (1) in the IEEE 39 system, MRDMGWOA reduces the power generation cost and CO₂ emission by 17% and 22%, respectively, and reduces the computation time by 16.14 s compared with the centralized optimization; (2) in the IEEE 118 system, the two metrics are further optimized, with a 20% and 17% reduction in the cost and emission, respectively, and an improvement in the computational efficiency by 45.46 s; (3) in the spacing, hypervolume, and Euclidian metrics evaluation, MRDMGWOA outperforms other algorithms; (4) compared with the existing DMOGWO and DMOMFO, the computation time of MRDMGWOA is reduced by 177.49 s and 124.15 s, respectively, and the scheduling scheme obtained by MRDMGWOA is more optimal than DMOGWO and DMOMFO.…”
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A Robust Salp Swarm Algorithm for Photovoltaic Maximum Power Point Tracking Under Partial Shading Conditions by Boyan Huang, Kai Song, Shulin Jiang, Zhenqing Zhao, Zhiqiang Zhang, Cong Li, Jiawen Sun

“…Finally, the integration with P&O facilitates a meticulous search with a small step size, ensuring swift convergence and further mitigating post-convergence power oscillations. Both the simulations and the experimental results indicate that the proposed algorithm outperforms particle swarm optimization (PSO) and grey wolf optimization (GWO) in terms of convergence velocity, tracking precision, and the reduction in iteration power oscillation magnitude.…”
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An effectiveness of machine learning models for estimate the financial cost of assistive services to disability care in the Kingdom of Saudi Arabia by Obaid Algahtani, Mohammed M. A. Almazah, Farouq Alshormani

“…Eventually, the modified pelican optimization algorithm (MPOA) is utilized to fine-tune the optimal hyperparameter of ensemble model parameters to achieve high predictive performance. …”
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A Bi-Level Optimization Scheme for Energy Storage Configuration in High PV-Penetrated Distribution Networks Based on Improved Voltage Sensitivity Strategy by Bo Gao, Qing Du, Gonghao Zhan, Jian Han

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