Hybrid genetic algorithm to minimize scheduling cost with unequal and job dependent earliness tardiness cost by Prasad Bari, Prasad Karande, Vaidehi Bag

“…This article presents two combinatorial genetic algorithms (GA), unequal earliness tardiness-GA (UET-GA) and job-dependent earliness tardiness-GA (JDET-GA) for the single-machine scheduling problem to minimize earliness tardiness (ET) cost. …”
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RSM-YOLOv11: Lightweight Steel Surface Defect Segmentation Algorithm Research Based on YOLOv11 Improvement by Zenghai Shan, Hu Haoyan, Changjian Zhu, Shaowen Du, Hongtao Jing, Wang Haibin

“…The model size is reduced by 23.81%, and the computational cost is decreased by 15.38%. While maintaining a lightweight structure, it outperforms existing mainstream algorithm models. …”
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Chaotic Mountain Gazelle Optimizer Improved by Multiple Oppositional-Based Learning Variants for Theoretical Thermal Design Optimization of Heat Exchangers Using Nanofluids by Oguz Emrah Turgut, Mustafa Asker, Hayrullah Bilgeran Yesiloz, Hadi Genceli, Mohammad AL-Rawi

“…This theoretical research study proposes a novel hybrid algorithm that integrates an improved quasi-dynamical oppositional learning mutation scheme into the Mountain Gazelle Optimization method, augmented with chaotic sequences, for the thermal and economical design of a shell-and-tube heat exchanger operating with nanofluids. …”
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A new approach for bin packing problem using knowledge reuse and improved heuristic by Jie Fang, Xubing Chen, Yunqing Rao, Yili Peng, kuan Yan

“…The classic packing solution is a hybrid algorithm based on heuristic positioning and meta-heuristic sequencing, which has the problems of complex solving rules and high time cost. …”
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Integrated decision support system for optimizing time and cost trade offs in linear repetitive construction projects by Ahmed Gouda Mohamed, Ali Hassan Ali, Ahmed Adel Abdelhady

“…Abstract Linear repetitive construction projects present unique challenges in optimizing both completion time and cost performance. …”
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Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs by Azamuddin Ab Rahman, Sakib Iqram Hamim

“…However, due to the limited battery capacity of sensor nodes, energy efficiency remains a critical challenge, especially since data transmission consumes the most energy. This study introduces an enhanced energy aware clustering approach that combines an improved K-Means algorithm with an adaptive distance threshold to optimize relay node selection and cluster formation. …”
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Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO by Enlai ZHANG, Yi CHEN, Liang SU, Ruoyu ZHONGLIAN, Xianyi CHEN, Shangfeng JIANG

“…Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. …”
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Optimization of costs in the enterprise. Effective strategies for business by N. Yu. Pracheva

“…The article is devoted to an effective methods of cost optimization in small business. All of them, used at the right time, make it possible to improve the situation and maximize profits by reducing costs.…”
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Emission prediction and optimization of methanol/diesel dual-fuel engines based on ITransformer-BiGRU and NSGA-III by Mingzhang Pan, Xinxin Cao, Changcheng Fu, Shengyou Liao, Xiaorong Zhou, Wei Guan

“…Finally, based on the obtained mathematical model, the 3rd Non-dominated Sorting Genetic Algorithm (NGSA-III) is used to adjust and optimize the control parameters. …”
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Error Analysis and Compensation of 3‒PTT Parallel Robot by CHEN Mingfang, LIANG Hongjian, WEI Songpo, HE Chaoyin

“…Then, the improved particle swarm optimization algorithm is utilized to optimize the error correction objective function, where the slider compensation is obtained, and the servo driver is utilized to complete the error compensation. …”
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Quad Rapidly-Exploring Random Tree Star Algorithm With Improved Potential Force for Unmanned Aerial Vehicle Path Planning by Peng Bian, Jiaming Fan, Yang Liu, Xia Chen, Yu Wang

“…Rapidly-exploring random tree star (RRT*) has attracted intensive attention in track planning due to its asymptotic optimal properties. However, the RRT* algorithm plans costly trajectory paths. …”
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Landing scheduling for carrier aircraft fleet considering bolting probability and aerial refueling by Genlai Zhang, Lei Wang, Zhilong Deng, Xuanbo Liu, Xichao Su, Haixu Li, Chen Lu, Kai Liu, Xinwei Wang

“…Aiming at an efficient solution, an improved firefly algorithm is designed by integrating multiple evolutionary operators. …”
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RE-BPFT: An Improved PBFT Consensus Algorithm for Consortium Blockchain Based on Node Credibility and ID3-Based Classification by Junwen Ding, Xu Wu, Jie Tian, Yuanpeng Li

“…Experimental results indicate that RE-BPFT markedly reduces consensus latency and communication costs while achieving higher throughput and better scalability than classical PBFT, RBFT, and PPoR algorithms. …”
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Multi-objective optimization of hybrid microgrid for energy trilemma goals using slime mould algorithm by Alok Kumar Shrivastav, Soham Dutta

“…Compared to conventional metaheuristic such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), the SMA achieves a power loss reduction of 12.3% and a levelized cost of energy (LCOE) improvement of 9.8%. …”
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A constructal theory framework for optimizing HRSG design: Enhancing thermal performance and cost-effectiveness by Morteza Mehrgoo, Majid Amidpour

“…These findings highlight the effectiveness of Constructal Theory in determining the optimal HRSG Type and precise geometric design for various gas turbine specifications, resulting in substantial improvements in energy recovery and cost efficiency.…”
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Enhanced air quality prediction using adaptive residual Bi-LSTM with pyramid dilation and optimal weighted feature selection by R. Sudha, Ajith Damodaran, Gunaselvi Manohar

“…The proposed model introduces a novel methodology for weighted feature selection utilizing an Improved Gannet Optimization Algorithm (IGOA) aimed at enhancing the performance of data classification. …”
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Economic energy optimization in microgrid with PV/wind/battery integrated wireless electric vehicle battery charging system using improved Harris Hawk Optimization by Perne Mallikarjun, Sundar Rajan Giri Thulasiraman, Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri

“…The study adopts an Improved Harris Hawk Optimization (IHHO) algorithm to optimize energy management and minimize operational costs under varying scenarios. …”
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A multi-objective improved horse herd optimizer based on convex lens imaging for stochastic optimization of wind energy resources in distribution networks considering reliability a... by Fude Duan, Ali Basem, Dheyaa J. Jasim, Mahdiyeh Eslami, Mustafa Okati

“…The Multi-Objective Improved Horse Herd Optimizer (MOIHHO) is derived from an enhanced version of the traditional horse herd optimizer. …”
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An Improved Particle Swarm Optimization and Adaptive Neuro-Fuzzy Inference System for Predicting the Energy Consumption of University Residence by Stephen Oladipo, Yanxia Sun, Oluwatobi Adeleke

“…To address this problem, the velocity update equation of the original PSO algorithm is modified by incorporating a dynamic linear decreasing inertia weight, which improves the PSO algorithm’s convergence behaviour and aids both local and global search. …”
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A Novel Fault Diagnosis Method for Rolling Bearing Based on Improved Sparse Regularization via Convex Optimization by Dongjie Zhong, Cancan Yi, Han Xiao, Houzhuang Zhang, Anding Wu

“…To handle this difficulty, a novel fault signal denoising scheme based on improved sparse regularization via convex optimization is proposed to extract the fault feature of rolling bearing. …”
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