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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.

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

  • 会议论文

  • 发表日期：

    2025年

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

摘要

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.