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Determination Of The Optimal Process Means And Production Cycles For Multistage Production Systems Subject To Process Deterioration
Published 2020“…A Hook and Jeeves search algorithm is used to optimize the model, and a numerical example is provided. …”
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83
Energy conversion of heat from abandoned oil wells to mechanical refrigeration - Transient analysis and optimization
Published 2021“…Among 43 investigated refrigerants, R1234ze(E) has higher efficiency, lower Pumping Work Ratio (PWR), and requires a smaller size of the heat exchangers. Using the genetic algorithm optimization method with R1234ze(E) as working fluid in both power and cooling loops, a maximum power loop efficiency of 6.3% and COP of 5.3 were obtained at a high pressure of 29 bar (in the power loop) with minimal expander diameter of 64, compressor diameter of 171 mm, and 18 expander-compressor units.…”
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Finite state machine state assignment for area and power minimization
Published 2006“…In this paper, we address the problem of FSM state assignment to minimize area and power. The objectives are targeted as single/independent as well as multi-objective optimization (MOP) problems. …”
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85
High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm
Published 2025“…These strategies leverage various sinusoidal and cosinusoidal factors to improve the algorithm. The optimization goal is to minimize sum square error (SSE) between measured and simulated stack voltages. …”
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Integrated economic and environmental models for a multi stage cold supply chain under carbon tax regulation
Published 2017“…The structural properties for the optimal solution of the three models are identified and solution algorithms are also proposed. …”
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87
ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation
Published 2022“…The best solutions adopted in this situation are often based on optimization algorithms that generate the controller’s gains in each period where there is an internal or external perturbation, adapting the behaviors of the PID against the system’s nonlinearity. …”
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Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach
Published 2023“…Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …”
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…Coupling the developed MLPNN and differential evolution optimization algorithm shows that temperature = 263 K and pressure = 6.92 MPa are the optimum condition for minimizing the MeOH loss in the gas hydrate prevention unit. …”
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An efficient claim management assurance system using EPC contract based on improved monarch butterfly optimization models
Published 2024“…To address these challenges, a claim management system is developed based on the Improved Monarch Butterfly Optimization Algorithm (IMBOA) and the principles of EPC. …”
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One-Machine Scheduling To Minimize Mean Tardiness With Minimum Number Tardy
Published 2020“…It is proved that the schedule generated by the proposed algorithm is indeed optimal.…”
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One-Machine Scheduling To Minimize Mean Tardiness With Minimum Number Tardy
Published 2020“…It is proved that the schedule generated by the proposed algorithm is indeed optimal.…”
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94
Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
Published 2025“…Furthermore, the reduction in sideslip angle, excellent traction through minimizing tire slip ratio, avoiding oversteering and understeering, and maintaining an acceptable range of energy optimization are demonstrated for DRL controllers, especially for the TD3 and CL TD3 algorithms.…”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities
Published 2021“…To solve the proposed model, four meta-heuristic algorithms, namely multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), a hybrid of k-medoids as a famous clustering algorithm and NSGA-II (KNSGA-II), and a hybrid of K-medoids and MOPSO (KMOPSO) are implemented. …”
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A fix and optimize method based approximate dynamic programming approach for the strategic fleet sizing and delivery planning problem
Published 2024“…In this study, we suggest an approximate Dynamic Programming algorithm, with a look ahead strategy, that uses the fix and optimize method as the imbedded heuristic for solving integrated fleet composition and replenishment planning problem. …”
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Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
Published 2017Get full text
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A utility minimization approach for energy-aware cooperative content distribution with fairness constraints
Published 2012“…Thus, to ensure fairness in energy consumption, a low complexity utility minimization algorithm is proposed. Using the appropriate utilities, the algorithm can be used to implement the optimal greedy energy minimization solution or to ensure different degrees of fairness in energy consumption. …”
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Enhanced DC Microgrid Protection: a Neural Network and Wavelet Transform Approach
Published 2024Get full text
doctoralThesis