Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

Combinatorial optimization problems are encountered often in various real-world applications, including logistics, scheduling, and network design ...

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 ...

This repository contains metaheuristic algorithm implementations for solving the Team Formation Problem (TFP). Developed as part of the Bachelor Thesis project: "Balancing diversity and preferences: ...

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 ...

In this research article, we uphold the principles of the No Free Lunch theorem and employ it as a driving force to introduce an innovative game-based metaheuristic technique named Golf Optimization ...

As the world moves towards industrialization, optimization problems become more challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms (MAs) have been developed to date, ...

ABSTRACT: This paper aimed to present the optimization of energy resource management in a car factory by the adaptive current search (ACS)—one of the most efficient metaheuristic optimization search ...