Optimizing Vehicle Routing for Perishable Products with Time Window Constraints: by Rifqi Fauzi, Adi Priansyah, Paskalis Krisna Puspadewa, Syifa Maulvi Zainun Awal, Huu Tho Nguyen, Achmad Pratama Rifai

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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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Path Planning of Underground Robots via Improved A* and Dynamic Window Approach by Jianlong Dai, Yinghao Chai, Peiyin Xiong

“…To overcome these challenges, we propose an improved path planning algorithm integrating an enhanced A* method with an improved Dynamic Window Approach (DWA). …”
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Enhanced Search Spring Algorithm for Green Agri-Food Supply Chain Network Design by Xiaoya Hu

“…In light of these challenges, this study presents a new Enhanced Search Spring Algorithm (ESSA), which optimizes GASCN by minimizing total transportation costs and is characterized by improved solution quality and computational efficiency. …”
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Application of Multi-Objective Optimization for Path Planning and Scheduling: The Edible Oil Transportation System Framework by Chin S. Chen, Chia J. Lin, Yu J. Lin, Feng C. Lin

“…The method employs the A* and Dijkstra pathfinding algorithm to determine the shortest pipeline route for each task, and estimates pipeline resource usage to derive a node cost weight function. …”
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Mathematical modelling and optimization of cutting conditions in turning operation on MDN 350 steel with carbide inserts by Syed Adil, A. Krishnaiah, D. Srinivas Rao

“…Improvement of tool life, enhancement of rate of production, reduction in cost of production and closeness of surface finish to that of grinding are the major goals of the work. …”
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AquaFlowNet a machine learning based framework for real time wastewater flow management and optimization by P. Prabu, Ala Saleh Alluhaidan, Romana Aziz, Shakila Basheer

“…These limitations often lead to inefficiencies such as energy wastage, treatment delays, and overflow incidents, negatively impacting system performance and sustainability.AquaFlowNet leverages state-of-the-art machine learning algorithms to analyze real-time data from sensors, forecast flow variations, and optimize wastewater treatment processes. …”
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Multi-Objective Evolution and Swarm-Integrated Optimization of Manufacturing Processes in Simulation-Based Environments by Panagiotis D. Paraschos, Georgios Papadopoulos, Dimitrios E. Koulouriotis

“…Multiple objective functions are formulated to optimize the behavior of the system by reducing the work-in-progress items and improving both cost-effectiveness and service level. …”
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Assimilating Satellite-Based Biophysical Variables Data into AquaCrop Model for Silage Maize Yield Estimation Using Water Cycle Algorithm by Elahe Akbari, Ali Darvishi Boloorani, Jochem Verrelst, Stefano Pignatti

“…Based on our proposed workflow in previous studies, a Gaussian process regression–particle swarm optimization (GPR-PSO) algorithm and global sensitivity analysis were applied to retrieve the fCover and biomass from Sentinel-2 satellite data and to identify the most sensitive parameters in the AquaCrop model, respectively. …”
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Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

“…Therefore, there is a pressing need to develop techniques for detecting early signs of depression to enable timely intervention and potentially improve recovery rates. In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
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Passenger Flow Prediction for Rail Transit Stations Based on an Improved SSA-LSTM Model by Xing Zhao, Chenxi Li, Xueting Zou, Xiwang Du, Ahmed Ismail

“…According to the experimental results, the proposed SSA-LSTM model has a more effective performance than the Support Vector Regression (SVR) method, the eXtreme Gradient Boosting (XGBoost) model, the traditional LSTM model, and the improved LSTM model with the Whale Optimization Algorithm (WOA-LSTM) in the passenger flow prediction. …”
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Optimization of delivery routes for takeout under time-varying road networks by Jiaci Wang, Liang Huang, Yuanqiao Wen, Yamin Huang, Man Zhu

“…This model is designed to effectively optimize the delivery plan, achieving a balance between delivery costs and customer satisfaction. …”
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Dynamic multi-criteria scheduling algorithm for smart home tasks in fog-cloud IoT systems by Ruchika Bhakhar, Rajender Singh Chhillar

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Multi-objective programming method for ship weather routing based on fusion of A* and NSGA-II by Yuankui LI, Jiyuan SUO, Dongye YU, Xinyu ZHANG, Fang YANG, Xuefeng YANG

“…ConclusionIn summary, the proposed method can be applied to optimize ship ocean routes under multiple constraint conditions and identify routes that meet the voyage objectives, thereby reducing operational costs, improving shipping efficiency and providing support for ship meteorological navigation and future intelligent ship navigation.…”
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Business Optimization of Financial Centers in Pharmaceutical Enterprises Based on Robotic Process Automation Technology by Yali Wang, Weiwei Zhou, Yingji Li, Jingqi Sun

“…The results indicate that the research designed business optimization method for pharmaceutical enterprise financial centers based on robot process automation technology significantly improves business processing efficiency, effectively controls costs, and enhances operational flexibility. …”
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Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

“…This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms. By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method and fuzzy entropy (FE) with the new and highly efficient Runge–Kuta optimizer (RUN), adaptive parameter optimization for the support vector machine (SVM) and radial basis function neural network (RBFNN) algorithms was achieved. …”
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Improved PICEA-g-based multi-objective optimization scheduling method for distribution network with large-scale electric vehicles by Meiyi Huo, Songling Pang, Hailong Zhao

“…Abstract Large-scale electric vehicle access to the distribution grid for charging can affect the security and economic operation of the grid. In this paper, an optimal scheduling method for large-scale EV access to the distribution grid based on the improved preference-inspired co-evolutionary algorithm using goal vectors (PICEA-g) is proposed. …”
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Multi-Objective Dynamic System Model for the Optimal Sizing and Real-World Simulation of Grid-Connected Hybrid Photovoltaic-Hydrogen (PV-H₂) Energy Systems by Ayatte I. Atteya, Dallia Ali, Nazmi Sellami

“…The model integrates a Particle Swarm Optimisation (PSO) algorithm that enables minimising both the levelised cost of energy (LCOE) and the building carbon footprint with a dynamic model that considers the real-world behaviour of the system components. …”
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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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Prediction and Optimization for Multi-Product Marketing Resource Allocation in Cross-Border E-Commerce by Yi Xie, Heng-Qing Ye, Wenbin Zhu

“…Experiments on real-world data show that our framework significantly outperforms baseline strategies, achieving a 14.48% increase in order volume and revenue improvements ranging from 0.19% to 43.91%. The minimum-cost flow algorithm consistently outperforms the greedy approach, especially in large-scale instances. …”
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