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constrained optimization » unconstrained optimization (Expand Search), inspired optimization (Expand Search)
policy optimization » capacity optimization (Expand Search)
constrained optimization » unconstrained optimization (Expand Search), inspired optimization (Expand Search)
policy optimization » capacity optimization (Expand Search)
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61
Evacuation of a highly congested urban city
Published 2017“…In this paper, we present a capacity-constrained routing optimization approach to maximize the total evacuees for short notice evacuation planning in case of both natural and/or man-made disasters. …”
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conferenceObject -
62
2022 IEEE Congress on Evolutionary Computation (CEC)
Published 2022“…We tested the performance of the proposed IMODEII by considering 12 benchmark functions with 10 and 20 variables taken from CEC2022 competition on single objective bound constrained numerical optimisation. A comparison between the proposed IMODEII and the state-of-the-art algorithms is conducted, with the results demonstrating the efficiency of the proposed IMODEII.…”
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63
Peak Loads Shaving in a Team of Cooperating Smart Buildings Powered Solar PV-Based Microgrids
Published 2021“…The main objective is to formulate a constrained optimization problem embedded in a model predictive control (MPC) scheme to optimally control the operation of each microgrid to reduce/shave the peak load in case of occurrence, optimizing the power flows exchanges and energy storages, while ensuring a high quality of service to the EVs owners in each microgrid. …”
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64
Spacecraft spin axis attitude determination
Published 1992“…Two algorithms are developed and compared by simulation. …”
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65
The multi-parameterized cluster editing problem
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66
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67
Reinforcement Learning-Based School Energy Management System
Published 2020“…After cloning the baseline strategy, the agent learns with proximal policy optimization in an actor-critic framework. …”
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68
A learning approach for prioritized handoff channel allocation in mobile multimedia networks
Published 2006“…Simulations are provided to compare the effectiveness of the proposed algorithm with other known resource-sharing policies such as complete sharing and reservation policies.…”
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69
Impacts of On-Grid Solar PV on Distribution Networks and Potential Solutions: A Case Study in the Region of Zahle
Published 2025“…The siting and sizing methodology is conducted by considering five different optimization algorithms, namely the single-objective genetic algorithm (SOGA), the combined SOGA and loss sensitivity factor algorithm (SOGA-LSF), the multi-objective genetic algorithm (MOGA), the combined MOGA-LSF and the CAPADD algorithm of OpenDSS. …”
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masterThesis -
70
AI-Augmented Metasurface Synthesis for Dynamic Beam Steering in Reconfigurable Antenna Arrays
Published 2025“…As compared to the conventional heuristic methods, for example, genetic algorithms (GA), particle swarm optimization (PSO), the approach based on DRLs has rapid policy convergence, has relatively less computational latency, and is autonomous to adapt to dynamic wireless conditions. …”
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71
Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
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doctoralThesis -
72
Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation
Published 2022“…A significant body of work in the literature employs differential privacy methods with constraining predefined parameters to achieve the optimal trade-off between privacy and utility of the data. …”
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73
UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks
Published 2018“…We formulate a joint optimization problem and divide it into four complementary subproblems to generate close-to-optimal results with lower complexity. …”
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74
3D deployment of UAVs in wireless networks for traffic offloading and edge computing. (c2019)
Published 2019“…This being said, computation tasks generated by IoT devices can be pro- cessed in less latency and with much lower energy consumption at the devices. To optimally deploy UAVs as mounted cloudlets, we formulate our problem as mixed integer program and then use an e cient meta-heuristic algorithm to generate optimized results for large scale IoT networks. …”
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masterThesis -
75
MoveSchedule
Published 1995“…The layout construction algorithm that underlies MoveSchedule uses Constraint Satisfaction to find the set of all positions that meet the constraints on resources' positions and Linear Programming to find the optimal positions that minimize resource transportation and relocation costs. …”
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masterThesis -
76
A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks
Published 2025“…We present a structured taxonomy covering value-based, policy-based, actor-critic, model-based, and advanced multi-agent and multi-objective approaches, and link algorithms to tasks such as dispatch, microgrid coordination, real-time pricing, load balancing, and demand–response. …”
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77
Hybrid deep learning based threat intelligence framework for Industrial IoT systems
Published 2025“…The proposed approach was also compared against several contemporary deep learning-based architectures and existing benchmark algorithms. The results indicate that the proposed method achieves superior detection accuracy, with only a minimal compromise in speed efficiency. …”
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78
Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters
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doctoralThesis