The Importance of Being Earnest: Multiple Heterogeneous Container Loading with a Simple Genetic Algorithm

Francesco Rusin*, Jan Fiala, Julian Sanker, Suyesh Bhattarai, Anikó Ekárt

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication

Abstract

In this study we address the complex practical problem of multiple heterogeneous container loading with a simple genetic algorithm. We demonstrate that with a well-chosen representation including a heuristic and a suitable fitness function the other aspects of the genetic algorithm do not need extensive work for good results. Following systematic study of our method on synthetically generated data, we visually showcase the solution for a company-based problem instance.

Original languageEnglish
Title of host publicationApplications of Evolutionary Computation
Subtitle of host publication28th European Conference, EvoApplications 2025, Held as Part of EvoStar 2025, Trieste, Italy, April 23-25, 2025, Proceedings, Part I
EditorsPablo García-Sánchez, Emma Hart, Sarah L. Thomson
Pages482-495
Number of pages14
ISBN (Electronic)9783031900624
DOIs
Publication statusPublished - 17 Apr 2025
Event28th European Conference on Applications of Evolutionary Computation, EvoApplications 2025, held as part of EvoStar 2025 - Trieste, Italy
Duration: 23 Apr 202525 Apr 2025

Publication series

NameLecture Notes in Computer Science (LNCS)
Volume15612
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference28th European Conference on Applications of Evolutionary Computation, EvoApplications 2025, held as part of EvoStar 2025
Country/TerritoryItaly
CityTrieste
Period23/04/2525/04/25

Keywords

  • genetic algorithm
  • heuristic
  • multiple heterogeneous container loading

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