Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

remove_circle_outline

Search Results (1)

Search Parameters:
Keywords = oil skimmer assignment

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
17 pages, 10191 KiB  
Article
Evolutionary Approach to Optimal Oil Skimmer Assignment for Oil Spill Response: A Case Study
by Yong-Hyuk Kim, Hye-Jin Kim, Dong-Hee Cho and Yourim Yoon
Biomimetics 2024, 9(6), 330; https://doi.org/10.3390/biomimetics9060330 - 30 May 2024
Cited by 1 | Viewed by 1699
Abstract
We propose a genetic algorithm for optimizing oil skimmer assignments, introducing a tailored repair operation for constrained assignments. Methods essentially involve simulation-based evaluation to ensure adherence to South Korea’s regulations. Results show that the optimized assignments, compared to current ones, reduced work time [...] Read more.
We propose a genetic algorithm for optimizing oil skimmer assignments, introducing a tailored repair operation for constrained assignments. Methods essentially involve simulation-based evaluation to ensure adherence to South Korea’s regulations. Results show that the optimized assignments, compared to current ones, reduced work time on average and led to a significant reduction in total skimmer capacity. Additionally, we present a deep neural network-based surrogate model, greatly enhancing efficiency compared to simulation-based optimization. Addressing inefficiencies in mobilizing locations that store oil skimmers, further optimization aimed to minimize mobilized locations and was validated through scenario-based simulations resembling actual situations. Based on major oil spills in South Korea, this strategy significantly reduced work time and required locations. These findings demonstrate the effectiveness of the proposed genetic algorithm and mobilized location minimization strategy in enhancing oil spill response operations. Full article
(This article belongs to the Special Issue Nature-Inspired Metaheuristic Optimization Algorithms 2024)
Show Figures

Figure 1

Back to TopTop