A Genetic Algorithm for Marine Spatial Planning with Minimized Conflict Between Planned Regions

Seo-Ah Yu, Choong-Ki Kim, Yong-Hyuk Kim

2023

Abstract

To efficiently utilize marine space, numerous experiments have been conducted to optimize marine space. We utilize a genetic algorithm (GA) to develop an optimal spatial plan for the Exclusive Economic Zone (EEZ). The space can be allocated for six different uses, each with its own weight. Conflicts exist among these uses. The objective is to maximize the fitness of the space by evaluating it at the cell level. This involves maximizing the evaluation score, which is determined by the weighted sum of each cell’s use, minimizing conflicts, and reducing the number of clusters to ensure continuity of use. The basic allocation model, which achieves the best quality among random solutions within the same running time as our GA, is used for comparison. Experimental results showed that, when our method is compared to the basic model, the evaluation scores increased by approximately 20%, except for one case of use ‘ecology’. Additionally, conflicts between zones decreased, and the total fitness improved as the number of clusters decreased.

Paper Citation

in Harvard Style

Yu S., Kim C. and Kim Y. (2023). A Genetic Algorithm for Marine Spatial Planning with Minimized Conflict Between Planned Regions. In Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: ECTA; ISBN 978-989-758-674-3, SciTePress, pages 179-185. DOI: 10.5220/0012165000003595

in Bibtex Style

@conference{ecta23,
author={Seo-Ah Yu and Choong-Ki Kim and Yong-Hyuk Kim},
title={A Genetic Algorithm for Marine Spatial Planning with Minimized Conflict Between Planned Regions},
booktitle={Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: ECTA},
year={2023},
pages={179-185},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012165000003595},
isbn={978-989-758-674-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: ECTA
TI - A Genetic Algorithm for Marine Spatial Planning with Minimized Conflict Between Planned Regions
SN - 978-989-758-674-3
AU - Yu S.
AU - Kim C.
AU - Kim Y.
PY - 2023
SP - 179
EP - 185
DO - 10.5220/0012165000003595
PB - SciTePress