Abstract: Automated design of metaheuristic algorithms offers an attractive avenue to reduce human effort and gain enhanced performance beyond human intuition. Current automated methods design ...

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Abstract: Feature selection is a critical and prominent task in machine learning. To reduce the dimension of the feature set while maintaining the accuracy of the performance is the main aim of the ...

ABSTRACT In this paper, we propose a multi-objective evolutionary metaheuristic approach based on the Pareto Ant Colony Optimization (P-ACO) metaheuristic and the non-dominated genetic sorting ...

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This Python package provides implementations of three metaheuristic algorithms to solve the Traveling Salesman Problem (TSP): Steepest Ascent Hill Climbing, Simulated Annealing, and Ant Colony ...

The Windows version of the Python interpreter can be run from the command line the same way it’s run in other operating systems, by typing python or python3 at the prompt. But there’s a feature unique ...

This paper introduces a new metaheuristic algorithm named the Osprey Optimization Algorithm (OOA), which imitates the behavior of osprey in nature. The fundamental inspiration of OOA is the strategy ...