Real-polarized genetic algorithm for the three-dimensional bin packing problem

Abstract

This article presents a non-deterministic approach to the Three-Dimensional Bin Packing Problem, using a genetic algorithm. To perform the packing, an algorithm was developed considering rotations, size constraints of objects and better utilization of previous free spaces (flexible width). Genetic operators have been implemented based on existing operators, but the highlight is the Real-Polarized crossover operator that produces new solutions with a certain disturbance near the best parent. The proposal presented here has been tested on instances already known in the literature and real instances. A visual comparison using boxplot was done and, in some situations, it was possible to say that the obtained results are statistically superior than the ones presented in the literature. In a given instance class, the presented Genetic Algorithm found solutions reaching up to 70% less bins.

Publication DOI: https://doi.org/10.1145/3071178.3071327
Divisions: College of Engineering & Physical Sciences
Additional Information: -
Event Title: Genetic and Evolutionary Computation Conference, GECCO '17
Event Type: Other
Event Dates: 2017-07-15 - 2017-07-19
ISBN: 978-1-4503-4920-8, 978-1-4503-4939-0
PURE Output Type: Conference contribution
Published Date: 2017-07-15
Accepted Date: 2017-07-01
Authors: Dornas, Andre Homem
Martins, Flávio Vinícius Cruzeiro
Sarubbi, João Fernando Machry
Wanner, Elizabeth Fialho (ORCID Profile 0000-0001-6450-3043)

Download

[img]

Version: Accepted Version

| Preview

Export / Share Citation


Statistics

Additional statistics for this record