Joint Inversion of Direct Current Resistivity and Seismic Refraction Data, using Local and Global Optimization Algorithms with Synthetic and Real Data Examples by unknown

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Joint Inversion of Direct Current Resistivity and Seismic Refraction Data, using Local and Global Optimization Algorithms with Synthetic and Real Data Examples by unknown

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Spark-based cooperative coevolution for large scale global optimization by Ahmad, Imtiaz

“…The cooperative coevolution framework was introduced to address the shortcomings of metaheuristic algorithms in solving continuous large-scale global optimization problems. …”
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Spark-based cooperative coevolution for large scale global optimization by Ahmad, Imtiaz

“…The cooperative coevolution framework was introduced to address the shortcomings of metaheuristic algorithms in solving continuous large-scale global optimization problems. …”
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GPU-based cooperative coevolution for large-scale global optimization by Ahmad, Imtiaz

“…The goal of researchers is to optimize the performance of algorithms in terms of both quality of solution and computational speed, seeing that large-scale optimization can be a computationally expensive process. …”
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An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications by Abu Zitar, Raed

“…The JAYA algorithm combines the survival of the fittest principle from evolutionary algorithms as well as the global optimal solution attractions of Swarm Intelligence methods. …”
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An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems by Abdel-Salam, Mahmoud

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Optimal VAR Dispatch Using a Multiobjective Evolutionary Algorithm by Abido, M. A.

“…In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dispatch problem is presented. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…”

A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions by Muhammad Shahid Wasim (16883984)

Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence by Atiq Ur Rehman (8843024)

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A Parallel Tabu Search Algorithm for Optimizing Multiobjective VLSI Placement by Minhas, Mahmood R.

“…In this paper, we present a parallel tabu search (TS) algorithm for efficient optimization of a constrained multiobjective VLSI standard cell placement problem. …”
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Multiobjective Optimal VAR Dispatch Using Strength Pareto Evolutionary Algorithm by Abido, M.A.

“…In this paper, strength Pareto evolutionary algorithm (SPEA) for optimal reactive power (VAR) dispatch problem is presented. …”
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Multiobjective optimal power flow using strength Pareto evolutionary algorithm by Abido, M.A.

“…In this paper, a novel multiobjective evolutionary algorithm for optimal power flow (OPF) problem is presented. …”
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A novel multiobjective evolutionary algorithm for optimal reactive power dispatch problem by Abido, M.A.

“…In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dispatch problem is presented. …”
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Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System by Mohamed Ali Zeddini (22047920)

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Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller by Sk. A., Shezan

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Design and analysis of entropy-constrained reflected residual vector quantization by Mousa, W.A.H.

“…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. Jointly optimized RVQ (JORVQ) is an effective design algorithm for minimizing the overall quantization error. …”
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Enhancing the Local Search Ability of the Brain Storm Optimization Algorithm by Covariance Matrix Adaptation by El-Abd, Mohammed

“…Recently, the Brain Storm Optimization (BSO) algorithm has attracted many researchers and practitioners attention from the evolutionary computation community. …”
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Optimal Management of Mobile Energy Generation and Storage Systems by Samara, Sarra Mahmoud

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