An Experimental Study of Strategies to Control Diversity in Grouping Mutation Operators: An Improvement to the Adaptive Mutation Operator for the GGA-CGT for the Bin Packing Problem

An Experimental Study of Strategies to Control Diversity in Grouping Mutation Operators: An Improvement to the Adaptive Mutation Operator for the GGA-CGT for the Bin Packing Problem

Grouping Genetic Algorithms (GGAs) are among the most outstanding methods for solving NP-hard combinatorial optimization problems by efficiently grouping sets of items. Their performance depends on problem-specific heuristics and a balance between exploration and exploitation. The mutation operator...

Full description

Saved in:
Bibliographic Details
Main Authors: Stephanie Amador-Larrea, Marcela Quiroz-Castellanos, Octavio Ramos-Figueroa
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Mathematical and Computational Applications
Subjects:
bin packing problem
grouping genetic algorithm
mutation operator
adaptive control
Online Access:https://www.mdpi.com/2297-8747/30/2/31
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2297-8747/30/2/31

Similar Items