SOE: A Multi-Objective Traffic Scheduling Engine for DDoS Mitigation with Isolation-Aware Optimization by Mingwei Zhou, Xian Mu, Yanyan Liang

“…When interception fails, effectively allocating mixed benign and malicious traffic under resource constraints becomes a critical challenge. To address this, we propose SchedOpt Engine (SOE), a scheduling framework formulated as a discrete multi-objective optimization problem. …”
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Advanced Sales Route Optimization Through Enhanced Genetic Algorithms and Real-Time Navigation Systems by Wilmer Clemente Cunuhay Cuchipe, Johnny Bajaña Zajia, Byron Oviedo, Cristian Zambrano-Vega

“…Efficient sales route optimization is a critical challenge in logistics and distribution, especially under real-world conditions involving traffic variability and dynamic constraints. …”
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Performance analysis of a filtering variational quantum algorithm by Gabriel Marin-Sanchez, David Amaro

“…Even a minor boost in solving combinatorial optimization problems can greatly benefit multiple industries. …”
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A Hybrid Genetic Algorithm and Proximal Policy Optimization System for Efficient Multi-Agent Task Allocation by Zimo Zhu, Chuanqiang Yu, Junti Wang

“…Efficient task allocation remains a fundamental challenge in multi-agent systems, particularly under resource constraints and large-scale deployments. Classical methods, including market-based mechanisms, centralized optimization techniques, and game-theoretic strategies, have been widely applied to address the multi-agent task allocation problem. …”
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OPTIMIZING LAST-MILE DELIVERY BY DEEP Q-LEARNING APPROACH FOR AUTONOMOUS DRONE ROUTING IN SMART LOGISTICS by Pannee Suanpang, Pitchaya Jamjuntr

“…At last, it advocates carrying on deeper into the application of reinforcement learning in the solving of complex optimization problems in various other fields. …”
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OPTIMIZING LAST-MILE DELIVERY BY DEEP Q-LEARNING APPROACH FOR AUTONOMOUS DRONE ROUTING IN SMART LOGISTICS by Pannee Suanpang, Pitchaya Jamjuntr

“…At last, it advocates carrying on deeper into the application of reinforcement learning in the solving of complex optimization problems in various other fields. …”
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Enhancing intrusion detection in wireless sensor networks using a Tabu search based optimized random forest by Vivek Kumar Pandey, Shiv Prakash, Tarun Kumar Gupta, Priyanshu Sinha, Tiansheng Yang, Rajkumar Singh Rathore, Lu Wang, Sabeen Tahir, Sheikh Tahir Bakhsh

“…To address this problem, Random Forest (RF) is a popular machine learning model. …”
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Power-Efficient UAV Positioning and Resource Allocation in UAV-Assisted Wireless Networks for Video Streaming with Fairness Consideration by Zaheer Ahmed, Ayaz Ahmad, Muhammad Altaf, Mohammed Ahmed Hassan

“…The aim of this research is to maximize the overall users’ quality of experience in terms of power-efficient adaptive video streaming by fair distribution and smooth transition of video rates. The joint optimization includes power minimization, efficient resource allocation, i.e., transmit power and bandwidth, and efficient two-dimensional positioning of the UAV while meeting system constraints. …”
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Estimating the Railway Network Capacity Utilization with Mixed Train Routes and Stopping Patterns: A Multiobjective Optimization Approach by Zhengwen Liao, Haiying Li, Jianrui Miao, Lingyun Meng

“…With the ε-constraint method, we can obtain the Pareto front of saturated timetables, i.e., a set of nondominated optimized timetables that no more candidate train can be additionally scheduled. …”
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Distributed dynamic event-triggered time-varying resource management for microgrids via practical predefined-time multiagent methods by Tingting Zhou, Salah Laghrouche, Youcef Ait-Amirat

“…To address this problem, a fully distributed predefined-time (PDT) optimization algorithm is developed, incorporating a time-base generator (TBG) to guarantee convergence within a PDT, independently of initial conditions and system parameters. …”
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Multi-objective stochastic model optimal operation of smart microgrids coalition with penetration renewable energy resources with demand responses by Ali Abdolahzadeh, Amir Hassannia, Farhoud Mousavizadeh, Mohammad Tolou Askari

“…A key innovation of this study is the development of an advanced hybrid solution methodology, combining the ε-constraint method for multi-objective optimization with Benders decomposition for computational efficiency. …”
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Multi-Objective Optimization Design of Low-Frequency Band Gap for Local Resonance Acoustic Metamaterials Based on Genetic Algorithm by Jianjiao Deng, Yunuo Qin, Xi Chen, Yanyong He, Yu Song, Xinpeng Zhang, Wenting Ma, Shoukui Li, Yudong Wu

“…The proposed multi-objective optimization framework is highly general and extensible and capable of effectively balancing between the acoustic performance and structural mass, thus providing an efficient engineering solution for low-frequency noise control problems.…”
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Multi-Objective Cooperative Adaptive Cruise Control Platooning of Intelligent Connected Commercial Vehicles in Event-Triggered Conditions by Jiayan Wen, Lun Li, Qiqi Wu, Kene Li, Jingjing Lu

“…Additionally, adaptive particle swarm optimization (APSO) is employed during the optimization process to solve the optimal problem efficiently. …”
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A Generalized Benders Decomposition for Mixed-Integer Nonlinear Programming: Theory and Applications by Fadiah Hasna Nadiatul Haq, Diah Chaerani, Anita Triska

“…This paper comprehensively explains how to solve mixed-integer nonlinear programming (MINLP) models using the generalized benders decomposition (GBD) method. The MINLP problem is an optimization model in which some variables must be integers and the objective function or constraints are nonlinear.  …”
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Providing a Roadmap for the Adaption of Agricultural Sector to Water Scarcity Conditions (Case Study: Selected Crops of Tajan Basin, Iran) by H. Fouladi, H. Amirnejad, S. Shirzadi Laskookalayeh

“…Goal Programming (GP) is an extension of LP in which targets are specified for a set of constraints. …”
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Maximization of Fundamental Frequency of Composite Stiffened Hypar Shell with Cutout by Taguchi Method by Puja Basu Chaudhuri, Anirban Mitra, Sarmila Sahoo

“…Obtaining the best combination of design variables like degree of orthotropy, ply orientation, shallowness of the shell, and eccentricity of cutout of laminated shells leads to a problem of combinatorial optimization. This article attempts a numerical study of the free vibration response of composite stiffened hypar shells with cutout using finite element procedure and optimization of different parametric combinations based on the Taguchi approach. …”
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LUNA: Loss-Construct Unsupervised Network Adjustment for Low-Dose CT Image Reconstruction by Ritu Gothwal, Shailendra Tiwari, Shivendra Shivani

“…Reconstructing low-dose CT imaging deals with handling the inherent noise within the data, which makes it a complex mathematical problem known as an ill-posed inverse problem. Recent attention has shifted towards deep learning-based techniques in CT image reconstruction. …”
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Methodology of statistical synthesis and analysis methods for stochastic signal processing in multi-antenna radio direction finders by Eduard Tserne, Yevhen Holovynskyi, Olha Zhyla

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Research on Fast Spectrum Resonance Calculation Method Based on Subgroup Method by YU Rongjun, ZHAO Shouzhi, YANG Rui, SONG Yingyun, ZHANG Chong, HUO Xingkai

“…One of the key steps of the subgroup method was to solve the subgroup parameters, combined with the particle swarm optimization to solve the subgroup parameters of the pseudo resonance nuclide and the subgroup parameters of each sub-resonance nuclide composed of it, and the obtained subgroup parameters had high precision, and at the same time, due to the constraints added to the value range of the variables in the solution process, the shortcomings of the traditional method such as numerical instability and initial value sensitivity could be effectively avoided. …”
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Gradient Boosting Feature Selection for Integrated Fault Diagnosis in Series-Compensated Transmission Lines by Rab Nawaz, Abdul Wadood, Khawaja Khalid Mehmood, Syed Basit Ali Bukhari, Hani Albalawi, Aadel Mohammed Alatwi, Muhammad Sajid

“…By optimizing each phase of data processing from feature extraction to model learning, the proposed system effectively addresses fault detection, classification, and localization as a multi-classification problem. …”
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