Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches by Kassem Danach, Louai Saker, Hassan Harb

“…This study addresses the optimization of the Vehicle Routing Problem (VRP) with prioritized customers by introducing and comparing two advanced solution approaches: a metaheuristic-based hyperheuristic framework and a Variational Autoencoder (VAE)-based hyperheuristic. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir, Aiman Erbad, Bechir Hamdaoui, Samir Brahim Belhaouari, Mohsen Guizani, Thang X. Vu

“…However, the IIoT inference distribution raises challenges in ensuring reliable data transmission with minimal latency while respecting the practical UAVs’ constraints. To address these issues, we formulate the problem of CNN layer distribution and UAV trajectory planning (LDTP) as an optimization problem to improve latency, reliability, and resource usage. …”
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Fast Task Scheduling With Model Predictive Control Integrating a Priority-Based Heuristic by Francesco Liberati, Manuel Donsante, Chiara Maria Francesca Cirino, Andrea Tortorelli

“…The algorithm shall suggest to the planning operators an optimized scheduling of the activities, i.e., one which minimizes the total completion time (the makespan), while satisfying all the applicable constraints. …”
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A critical review on phasor measurement units installation planning and application in smart grid environment by Vivekananda Pattanaik, Binaya Kumar Malika, Subhasis Panda, Pravat Kumar Rout, Binod Kumar Sahu, Indu Sekhar Samanta, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…Also, the problem formulation for the PMUs placement is expressed, giving importance to the objective function, constraints, variables, and assessment index reflecting the optimality in placement. …”
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Delineations for Police Patrolling on Street Network Segments with <i>p</i>-Median Location Models by Changho Lee, Hyun Kim, Yongwan Chun, Daniel A. Griffith

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Low-Resolution Quantized Precoding for Multiple-Input Multiple-Output Dual-Functional Radar–Communication Systems Used for Target Sensing by Xiang Feng, Zhongqing Zhao, Jiongshi Wang, Jian Wang, Zhanfeng Zhao, Zhiquan Zhou

“…Due to the complexity introduced by discrete constraints, we decompose the original problem into three sub-problems to reduce computational burden. …”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…The swarm intelligent optimization methods transform a complex problem of structural parameter identification into a constrained optimization problem. …”
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A Flexible Interconnected Distribution Network Power Supply Restoration Method Based on E-SOP by Lin Jiang, Canbin Wang, Wei Qiu, Hui Xiao, Wenshan Hu

“…The optimization problem is transformed into a second-order cone programming formulation under comprehensive operational constraints. …”
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Electric Vehicle Energy Management Under Unknown Disturbances from Undefined Power Demand: Online Co-State Estimation via Reinforcement Learning by C. Treesatayapun, A. J. Munoz-Vazquez, S. K. Korkua, B. Srikarun, C. Pochaiya

“…This paper presents a data-driven energy management scheme for fuel cell and battery electric vehicles, formulated as a constrained optimal control problem. The proposed method employs a co-state network trained using real-time measurements to estimate the control law without requiring prior knowledge of the system model or a complete dataset across the full operating domain. …”
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HAPS-ISAC: Enhancing Sensing and Communication in 6G Networks With Advanced MIMO Beamforming by Parisa Kanani, Mohammad Javad Omidi, Mahmoud Modarres-Hashemi, Halim Yanikomeroglu

“…The performance of the system is optimized through a non-convex optimization problem that maximizes the minimum beampattern gain towards desired sensing angles while ensuring that the signal-to-interference-plus-noise ratio (SINR) requirements for CUs are satisfied, all under the power constraints of the HAPS. …”
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Decision-maker’s behavioral preferences modeling in fuzzy goal programming through linear-nonlinear membership functions by Mohamed Sadok Cherif

“…A relevant extension of traditional goal programming (GP), fuzzy goal programming (FGP) can handle uncertainty and imprecision in multi-objective optimization problems. …”
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New Heuristic Local Search Method for University Course Timetabling by Mohammad Sadegh Shiri, Mostafa Khorramizadeh, Vahid Ahmadi

“…While the fitness function of the first phase is based on the violation of hard constraints, the fitness function of the second phase is based on the penalty of the feasible solution.Findings: The numerical results indicate that the required computing time increases with the size of instances, and the algorithm tends to converge towards the optimal solution after a few minutes.Originality/Value: The presented algorithm enables us to deal with extensive university course timetabling problems in practice. …”
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FACTS Controllers’ Contribution for Load Frequency Control, Voltage Stability and Congestion Management in Deregulated Power Systems over Time: A Comprehensive Review by Muhammad Asad, Muhammad Faizan, Pericle Zanchetta, José Ángel Sánchez-Fernández

“…Therefore, there is a trade-off between the selection and cost of FACTS devices to minimize the power system problems. Likewise, meta-heuristics and hybrid optimization techniques are commonly adopted to optimize FACTS devices due to their fast convergence, robustness, higher accuracy, and flexibility.…”
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Model Predictive Control With Reinforcement Learning-Based Speed Profile Generation in Racing Simulator by Min-Seong Kim, Tae-Hyoung Park

“…Model Predictive Control (MPC) is a widely used optimal control strategy, particularly effective in managing complex constraints. …”
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Deep Reinforcement Learning for RIS-Assisted Multi-UAV MU-MISO Communication Networks: Sum-Rate and Energy Efficiency Maximization by Alif Rahmatullah Umar, Hasan Albinsaid, Chia-Po Wei, Chih-Peng Li

“…We formulate separate optimization problems for sum-rate and energy efficiency, and address them using deep reinforcement learning (DRL) algorithms, namely proximal policy optimization (PPO) and deep deterministic policy gradient (DDPG). …”
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A Self-Learning Hyper-Heuristic Algorithm Based on a Genetic Algorithm: A Case Study on Prefabricated Modular Cabin Unit Logistics Scheduling in a Cruise Ship Manufacturer by Jinghua Li, Ruipu Dong, Xiaoyuan Wu, Wenhao Huang, Pengfei Lin

“…Hyper-heuristic algorithms are known for their flexibility and efficiency, making them suitable for solving engineering optimization problems with complex constraints. This paper introduces a self-learning hyper-heuristic algorithm based on a genetic algorithm (GA-SLHH) designed to tackle the logistics scheduling problem of prefabricated modular cabin units (PMCUs) in cruise ships. …”
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Smooth likelihood-based collision avoidance for polygon shaped and differential drive vehicles by Yang Zhou, Linjie Kong

“…The constrained optimal control problem is reformulated to improve the smoothness and efficiency. …”
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Nodal frequency-constrained energy storage planning via hybrid data-model driven methods by Jiaxin Wang, Jiawei Zhang, Min Yang, Yating Wang, Ning Zhang

“…Finally, we achieve optimal energy storage planning with both COI and nodal frequency constraints. …”
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Train timetable and stopping plan generation based on cross-line passenger flow in high-speed railway network by Yuqiang Wang

“…In addition, we regard train disturbances in different directions as different train headways at cross-line stations to optimize train scheduling practically. Sequentially, a mixed-integer linear programing model with headway and coupling constraints is formulated. …”
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Task Allocation and Path Planning Method for Unmanned Underwater Vehicles by Feng Liu, Wei Xu, Zhiwen Feng, Changdong Yu, Xiao Liang, Qun Su, Jian Gao

“…Cooperative operations of Unmanned Underwater Vehicles (UUVs) have extensive applications in fields such as marine exploration, ecological observation, and subsea security. …”
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