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Spider monkey optimizations: application review and results
Published 2024Subjects: “…Spider monkey…”
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Social spider optimization algorithm: survey and new applications
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A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems
Published 2021“…The test suite of benchmark function is recently designed for the special session of EAs competition in IEEE Congress on Evolutionary Computation (IEEE-CEC′13). The suggested algorithm has approximated promising solutions with good convergence and diversity maintenance for most of the used bound constrained single optimization problems. …”
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Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems
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An evolutionary algorithm for solving the geometrically constrained site layout problem
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Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities
Published 2002“…loosely versus tightly constrained layouts. In most problems considered where the total-objects-to-site-area ratio did not exceed 60%, the algorithm returned close to optimal solutions in a reasonable time.…”
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Whale optimization algorithm: analysis and full survey
Published 2024“…Various adaptations and hybridizations of the WOA are reviewed, including adaptive strategies, constrained and multiobjective optimization extensions, and combinations with other algorithms. …”
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Squirrel Search Algorithm for Portfolio Optimization
Published 2019“…In this paper, we design and adapt a Squirrel Search Algorithm (SSA) for the unconstrained and constrained portfolio optimization problems. …”
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Optimization of Support Structures for Offshore Wind Turbines using Genetic Algorithm with Domain-Trimming (GADT)
Published 2017“…The powerful genetic algorithm optimization technique is augmented with an innovative “domain-trimming” modification. …”
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Optimal VAR Dispatch Using a Multiobjective Evolutionary Algorithm
Published 2005“…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
Published 2025“…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.…”
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A Parallel Tabu Search Algorithm for Optimizing Multiobjective VLSI Placement
Published 2005“…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
Published 2020“…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
Published 2004“…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
Published 2003“…In this paper, a novel multiobjective evolutionary algorithm for optimal reactive power (VAR) dispatch problem is presented. …”
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Design and analysis of entropy-constrained reflected residual vector quantization
Published 2002“…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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UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices
Published 2019“…Then, we develop an effective sub-optimal algorithm based on successive convex approximation in order to obtain results for larger network scenarios. …”
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