Evolutionary estimation of distribution algorithm for agricultural routing planning in field logistics

Amalia Utamima*, Torsten Reiners, Amir H. Ansaripoor

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

15 Citations (Scopus)

Abstract

Agricultural Routing Planning (ARP), a problem in field logistics, has the objective to minimize the headland distance used by machines when performing agricultural tasks. This study gathers for its datasets the data for several fields obtained from previous research. The Estimation of Distribution Algorithm (EDA) is an algorithm that employs a probabilistic model to produce candidate solutions. This paper extends the EDA to become the Evolutionary EDA that combines a general EDA, a neighborhood search, and an elitism technique. Evolutionary EDA is tested on the optimization of ARP. The experimental results show that Evolutionary EDA can get the same or outperform the solutions generated by previously applied algorithms on ARP problems.

Original languageEnglish
Pages (from-to)560-567
Number of pages8
JournalProcedia Computer Science
Volume161
DOIs
Publication statusPublished - 2019
Event5th Information Systems International Conference, ISICO 2019 - Surabaya, Indonesia
Duration: 23 Jul 201924 Jul 2019

Keywords

  • Agricultural routing planning
  • Estimation distribution algorithm
  • Evolutionary algorithm
  • Field logistics

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