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constrained optimization » unconstrained optimization (Expand Search), inspired optimization (Expand Search)
constrained optimization » unconstrained optimization (Expand Search), inspired optimization (Expand Search)
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Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems
Published 2022Subjects: Get full text
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A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems
Published 2021“…The suggested algorithm integrates the SI-based algorithms to evolve population and handle exploration versus exploitation issues. …”
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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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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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Whale optimization algorithm: analysis and full survey
Published 2024“…The whale optimization algorithm (WOA) is a metaheuristic algorithm inspired by the hunting behavior of humpback whales. …”
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Design and analysis of entropy-constrained reflected residual vector quantization
Published 2002“…Reflected residual vector quantization (RRVQ) is an alternative design algorithm for the RVQ structure with a smaller computation burden. …”
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Squirrel Search Algorithm for Portfolio Optimization
Published 2019“…However, the successes of nature-inspired algorithms in hard computational optimization problems have encouraged researchers to design and apply these algorithms for a variety of optimization problems. …”
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UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices
Published 2019“…We demonstrate the favourable characteristics of the proposed algorithms via extensive simulation results and analysis as a function of various system parameters, with benchmarking against two greedy algorithms based on distance and deadline metrics.…”
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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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A Parallel Tabu Search Algorithm for Optimizing Multiobjective VLSI Placement
Published 2005“…The primary purpose is to accelerate TS algorithm to reach near optimal placement solutions for large circuits. …”
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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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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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Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests
Published 2023“…This paper describes how trial-based dominance can totally order this two-variable dataset of outcomes so that traditional non-parametric methods can determine the better of two algorithms when one is faster, but less accurate than the other, i.e. when neither algorithm dominates. …”
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Meta-Heuristic Procedures for the Multi-Resource Leveling Problem with Activity Splitting
Published 2011Get full text
doctoralThesis