Dynamic appliance scheduling and energy management in smart homes using adaptive reinforcement learning techniques by Poonam Saroha, Gopal Singh, Umesh Kumar Lilhore, Sarita Simaiya, Monish Khan, Roobaea Alroobaea, Majed Alsafyani, Hamed Alsufyani

“…These dynamics are difficult for traditional systems to handle, but new developments in reinforcement learning and optimization may be able to help. The paper introduces a novel Demand Response (DR) method that integrates a Self-Adaptive Puma Optimizer Algorithm (SAPOA) with a Multi-Objective Deep Q-Network (MO-DQN), improving smart home energy consumption, cost, and user preferences management. …”
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Accounting of infiltration waters and the level of recharge of the root layer by groundwater when calculating the irrigation regime on drained lands by Mazhaysky Yuri, Pavlov Artyom

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Network- and Demand-Driven Initialization Strategy for Enhanced Heuristic in Uncapacitated Facility Location Problem by Jayson Lin, Shuo Yang, Kai Huang, Kun Wang, Sunghoon Jang

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Revolutionizing RPAS logistics and reducing CO2 emissions with advanced RPAS technology for delivery systems by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte, Richard C. Millar, Robert Walter Meyer

“…The use of the NSGA-II meta-heuristic method for validation enhances the credibility and practicality of the model. The optimization model’s performance over 250 generations shows rapid initial improvements in cost, time, risk, and battery usage, followed by stabilization, indicating efficient convergence and effective evolutionary computation. …”
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Framework for truck–RPAS hybrid models in last-mile delivery by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte

“…High-quality Pareto-optimal solutions are produced by the non-dominated sorting genetic algorithm II, which methodically manages trade-offs between the conflicting goals. …”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…The algorithm divides the population into two parts, using the non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization algorithm (MOPSO) for solving, with improvements to enhance the algorithm’s performance. …”
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Hybrid harbor seal and jellyfish optimization technique for selecting the optimal location of hybrid renewable energy system by Radwa S. A. Gad, Hegazy Zaher, H. Al-Wahsh, M. H. Eid, Wael M. AlMetwaly, Islam M. Abdelqawee

“…Abstract Availability of a dependable electricity source is essential for improving living standards. When designing a micro-grid system, two key factors must be considered: cost-effectiveness and service quality. …”
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Vehicle-routing problem for low-carbon cold chain logistics based on the idea of cost–benefit by Yan Liu, Fengming Tao, Rui Zhu

“…Therefore, based on the idea of cost–benefit, a comprehensive vehicle routing problem optimization model with the objective function of minimizing the cost of unit satisfied customer is presented. …”
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Stochastic Multi-objective Distribution Network Reconfiguration Considering Wind Turbines by Ehsan Azad Farsani, Mohsen Zare

“…The objectives of proposed DNR policy are minimization of active power losses, total electrical energy costs, and total emissions of the network. To solve the problem, an improved version of Honey Bee Mating Optimization (IHBMO) algorithm is implemented. …”
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THE ALGORITHM FOR THE TREATMENT OF PATIENTS WITH TREATMENT-RESISTANT HYPERTENSION AT THE OUTPATIENT STAGE by O. S. Kulbachuk, E. V. Sid, O. V. Soloviov, A. V. Piskun

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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…In addition, the multi-feature fusion and feature selection method is proposed to enhance the query cost information. The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…In addition, the multi-feature fusion and feature selection method is proposed to enhance the query cost information. The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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Dynamic parking space allocation at urban scale: Problem formulation and resolution by Hanae Errousso, Jihane El Ouadi, El Arbi Abdellaoui Alaoui, Siham Benhadou

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Research on SBMPC Algorithm for Path Planning of Rescue and Detection Robot by Lin-Lin Wang, Li-Xin Pan

“…Sampling-Based Model Predictive Control (SBMPC) algorithm is proposed basing on the construction of cost function and predictive kinematics model. …”
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Interior Point Algorithm for Multi-UAVs Formation Autonomous Reconfiguration by Wang Jian-hong, Rana Javed Masood

“…Combined with three kinds of cost functions, nonlinear dynamic equations, and four inequality constraints, one nonlinear multiobjective optimization problem is constructed. …”
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Multi-objective optimization of HESS control for optimal frequency regulation in a power system with RE penetration by Ousama M.T. Ajami, Rodney H.G. Tan, Mithulan Nadarajah, Farah Adilah Jamaludin, Adlan Bagus Pradana

“…The findings indicate that the Independently Optimized Virtual Synchronous Generator HESS (IO VSG-HESS) achieves the best settling time post-contingency but offers the least improvement in frequency nadir with an average of 0.31 %. …”
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A Global Path Planning Algorithm Based on Bidirectional SVGA by Taizhi Lv, Chunxia Zhao, Jiancheng Bao

“…This algorithm does not construct a visibility graph before the path optimization. …”
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Combining Parallel Stochastic Methods and Mixed Termination Rules in Optimization by Vasileios Charilogis, Ioannis G. Tsoulos, Anna Maria Gianni

“…In this study, a combination of termination criteria is proposed, utilizing three different criteria to end the algorithmic process. These criteria include measuring the difference between optimal values in successive iterations, calculating the mean value of the cost function in each iteration, and the so-called “DoubleBox” criterion, which is based on the relative variance of the best value of the objective cost function over a specific number of iterations. …”
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Hybrid Adaptive Sheep Flock Optimization and Gradient Descent Optimization for Energy Management in a Grid-Connected Microgrid by Sri Harish Nandigam, Krishna Mohan Reddy Pothireddy, K. Nageswara Rao, Surender Reddy Salkuti

“…Results demonstrate the efficiency of the proposed hybrid algorithm, achieving substantial improvements in energy efficiency and cost reduction compared to traditional methods like interior point optimization, gradient descent, branch and bound, and a population-based algorithm named Golden Jackal optimization. …”
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Timing synchronization algorithm based on clock skew estimation for WSN by Yi SUN, Lu-kun ZENG, Xin WU, Jun LU, Yue SUN

“…In order to solve the problem of poor synchronization stability on classical synchronization algorithm,high overhead on joint clock offset and skew correction synchronization algorithm in wireless sensor network,a timing syn-chronization algorithm based on clock skew estimation for WSN (CSMS) was proposed.The algorithm adopted low-overhead clock offset and skew estimation method to improve the synchronization precision and stability of paired node.At the same time of guaranteeing the stability and accuracy,it realized synchronization with the root node and the neighbors,and optimized synchronization overhead by using the combination of hierarchical network structure and radio listening.The experimental results show that the CSMS algorithm balances energy consumption,accuracy and stability of synchronization.…”
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