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Metaheuristic Optimization

In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem. For some examples, you can visit https://aliasgharheidari.com/Publications.html

Papers

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Showing 51–69 of 69 papers

TitleStatusHype
Water and Electricity Consumption Forecasting at an Educational Institution using Machine Learning models with Metaheuristic Optimization—0
Metaheuristics is All You Need—0
A Hybrid Algorithm for Metaheuristic Optimization—0
A Brief Overview of Physics-inspired Metaheuristic Optimization Techniques—0
Adaptive Plant Propagation Algorithm for Solving Economic Load Dispatch Problem—0
Adaptive Wind Driven Optimization Trained Artificial Neural Networks—0
A data-driven rutting depth short-time prediction model with metaheuristic optimization for asphalt pavements based on RIOHTrack—0
A general Framework for Utilizing Metaheuristic Optimization for Sustainable Unrelated Parallel Machine Scheduling: A concise overview—0
A Metaheuristic-Driven Approach to Fine-Tune Deep Boltzmann Machines—0
A metaheuristic multi-objective interaction-aware feature selection method—0
An Adaptive Simulated Annealing-Based Machine Learning Approach for Developing an E-Triage Tool for Hospital Emergency Operations—0
A New K means Grey Wolf Algorithm for Engineering Problems—0
A novel computational technique using coefficient diagram method for load frequency control in an interconnected power system—0
Applications of deep reinforcement learning to urban transit network design—0
A stochastic metapopulation state-space approach to modeling and estimating Covid-19 spread—0
A Study of Left Before Treatment Complete Emergency Department Patients: An Optimized Explanatory Machine Learning Framework—0
Benchmarking for Metaheuristic Black-Box Optimization: Perspectives and Open Challenges—0
Blindfolded Spider-man Optimization: A Single-Point Metaheuristics Suitable for Continuous and Discrete Spaces—0
Boosting the Efficiency of Metaheuristics Through Opposition-Based Learning in Optimum Locating of Control Systems in Tall Buildings—0
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