Computation Offloading Strategy Based on Improved Polar Lights Optimization Algorithm and Blockchain in Internet of Vehicles by Yubao Liu, Bocheng Yan, Benrui Wang, Quanchao Sun, Yinfei Dai

“…Aiming at the problems that traditional optimization algorithms tend to fall into, where local optimum in task offloading and edge computing nodes are exposed to the risk of data tampering, this paper proposes a secure offloading strategy that integrates the Improved Polar Lights Optimization algorithm (IPLO) and blockchain. …”
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New improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing system by Xiaoxiao Wei, Jiafan Sun, Haojin Jiao

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Improved Monarch Butterfly Optimization Algorithm Based on Opposition-Based Learning and Random Local Perturbation by Lin Sun, Suisui Chen, Jiucheng Xu, Yun Tian

“…Many optimization problems have become increasingly complex, which promotes researches on the improvement of different optimization algorithms. …”
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Omni-Channel Product Distribution Network Design by Using the Improved Particle Swarm Optimization Algorithm by Si Zhang, Heying Zhu, Xia Li, Yan Wang

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Coverage optimization of wireless sensor network utilizing an improved CS with multi-strategies by Sen-Yu Yang, Chang-Feng Chen, Kai-Qing Zhou, Yun Ou

“…This makes it well-suited for solving such complex optimization problems. Based on this, this study proposes an improved Cuckoo Search algorithm with multi-strategies (ICS-MS), motivated by the ‘no free lunch’ theorem’s implication that no single optimization strategy universally dominates. …”
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Enhanced Dung Beetle Optimizer-Optimized KELM for Pile Bearing Capacity Prediction by Bohang Chen, Mingwei Hai, Gaojian Di, Bin Zhou, Qi Zhang, Miao Wang, Yanxiu Guo

“…In response to the need for rapid and precise predictions of pile bearing capacity, this study introduces a kernel extreme learning machine (KELM) prediction model optimized through a multi-strategy improved beetle optimization algorithm (IDBO), referred to as the IDBO-KELM model. …”
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Optimized planning of electric vehicle charging infrastructure for grid performance improvement by Mohammad Reza Maghami, Ka Fei Thang, Arthur G. O. Mutambara, Ali Akbar Firoozi, Elnaz Yaghoubi, Mehdi Zareian Jahromi, Elaheh Yaghoubi

“…This paper presents a multi-objective optimization framework developed using particle swarm optimization (PSO) algorithm to determine optimal placement and capacity of EV charging infrastructures. …”
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An improved meta-heuristic algorithm to optimize the fractional-order controller for an industrial manipulator with a parallelogram structure by Nazila Nikdel

“…Numerical results show the satisfying performances of the proposed controller and the improved optimization algorithm.…”
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Analysis of algorithms of interference coding and improving the efficiency in the complex systems by Oleg Pavlovich Malofey, Alexander Olegovych Malofey, Anastasia Evgenievna Shangina

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Improving Performance of the Convolutional Neural Networks for Electricity Theft Detection by using Cheetah Optimization Algorithm by Hassan Ghaedi, Seyed Reza Kamel Tabbakh, Reza Ghaemi

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Structural Simulation Model Updating Based on Improved MCMC Algorithm and Surrogate Model by MIAO Ji, DUAN Liping, LIU Jiming, LIN Siwei, ZHAO Jincheng

“…The results show that WOA can significantly improve the stability and convergence speed of the MCMC algorithm, the updating efficiency can be improved by 13.9% at most, and the maximum frequency errors of the simply supported beam model and the three-story steel frame model updated by the WO-MH algorithm are 0.009% and 2.41%, respectively. …”
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Coal Price Forecasting Using CEEMDAN Decomposition and IFOA-Optimized LSTM Model by Zhuang Liu, Xiaotuan Li

“…Abstract This study introduces a novel hybrid forecasting model for coking coal prices, integrating complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and long short-term memory (LSTM) neural networks, enhanced by an improved fruit fly optimization algorithm (IFOA). The approach begins with CEEMDAN decomposing the coking coal price sequence into intrinsic mode functions (IMFs) and a residual component, effectively mitigating non-stationarity and nonlinearity. …”
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An Adaptive Fusion Path Tracking Strategy for Autonomous Vehicles Based on Improved ACO Algorithm by Jihan Zhang, Yuan Wang, Jinyan Hu, Hongwu You

“…Although methods based on dynamic models and optimization theory can improve tracking performance, most autonomous systems lack high-fidelity models and the complexity of optimization processes lead to increase computational burden. …”
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Improving kinetic model fitting for total titratable acidity in bananas using genetic algorithms by Alejandro Kevin Méndez Castillo, Elizabeth Contreras López, Jesús Guadalupe Pérez Flores, Laura García Curiel, Emmanuel Pérez Escalante, Karla Soto Vega, Carlos Ángel-Jijón, Alicia Cervantes Elizarrarás

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Multimodal Transport Path Selection of Cold Chain Logistics Based on Improved Particle Swarm Optimization Algorithm by Changjiang Zheng, Kai Sun, Yuhang Gu, Jinxing Shen, Muqing Du

“…An improved particle swarm optimization algorithm (IPSO) is introduced to address the model and is proven to retain a fast convergence rate and achieve outstanding solving accuracy through the experimental study. …”
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Feature selection using a multi-strategy improved parrot optimization algorithm in software defect prediction by Qi Fei, Guisheng Yin, Zhian Sun

“…The proposed approaches in this study hold significant practical value, particularly in improving software quality, optimizing testing resource allocation, and reducing maintenance costs, offering broad potential for application in real-world software engineering scenarios.…”
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Improving kernel ridge regression for medical data classification based on meta-heuristic algorithms

“…The development of meta-heuristic algorithms has helped in solving difficult issues. In this paper, the main improvement is included in the pelican optimization algorithm by applying elite opposite-based learning (EOBL) to improve population diversity in the search space for selecting the best hyperparameters. …”
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Shuffled Puma Optimizer for Parameter Extraction and Sensitivity Analysis in Photovoltaic Models by En-Jui Liu, Rou-Wen Chen, Qing-An Wang, Wan-Ling Lu

“…To address this challenge, a novel metaheuristic algorithm called shuffled puma optimizer (SPO) is deployed to perform parameter extraction and optimal configuration identification across four PV models. …”
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An improvement in the design process of sustainable peak power rating transformer for solar utility by Emir Yükselen, Ebrahim Rahimpour

“…Such upgrades are essential for transitioning to a zero-emission electricity system and developing green energy projects.In this paper, a transformer has been studied using a combination of electrical design and 3D finite element method simulation to evaluate various design parameters. An optimization study has been conducted using an innovative multi-objective genetic algorithm utilizing a cost function that factors in size and material costs to identify the most efficient and cost-effective design solutions.The proposed design method was then validated through thermal model simulations and experimental tests based on the photovoltaic load cycle. …”
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Research on site selection and capacity determination problem based on improved particle swarm algorithm by Xiaotong Mi, Qinyang Liu, Bo Geng, Yong Zhu

“…Abstract To promote the effective utilization of distributed power sources after grid connection and achieve the goal of maximizing energy transmission efficiency and minimizing cost, this paper proposes a scheme based on the integration of the improved particle swarm optimization algorithm and the improved ant colony optimization algorithm (IPSOACO). …”
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