Optimizing the Path Towards Plastic-Free Oceans

Increasing ocean plastic pollution is irreversibly harming ecosystems and human economic activities. We partner with a non-profit organization and use optimization to help clean up oceans from plastic faster. Specifically, we optimize the route of their plastic collection system in the ocean to maximize the quantity of plastic collected over time. We formulate the problem as a longest path problem in a well-structured graph. However, since collection directly impacts future plastic density, the corresponding edge lengths are non-linear polynomials. After analyzing the structural properties of the edge lengths, we propose a search-and bound method, which leverages a relaxation of the problem solvable via dynamic programming and clustering, to efficiently find high-quality solutions (within 6%-optimal in practice), and develop a tailored branch-and-bound strategy to solve it to provable optimality. On one-year of ocean data, our optimization-based routing approach increases the quantity of plastic collected by over 60% compared with their current routing strategy, hence speeding up the progress towards plastic-free oceans. Supplemental Material: All supplemental materials, including the code, data, and files required to reproduce the results were reviewed and are available at [https://doi.org/10.1287/opre.2023.0515](https://doi.org/10.1287/opre.2023.0515)

Publication Details

Journal
London Business School Research Online (London Business School)
Published
2025-05-01
Primary Topic
Gyrotron and Vacuum Electronics Research
Type
article
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article

Optimizing the Path Towards Plastic-Free Oceans

London Business School Research Online (London Business School)
Gyrotron and Vacuum Electronics Research
article

Optimizing the Path Towards Plastic-Free Oceans

article en

Abstract

Increasing ocean plastic pollution is irreversibly harming ecosystems and human economic activities. We partner with a non-profit organization and use optimization to help clean up oceans from plastic faster. Specifically, we optimize the route of their plastic collection system in the ocean to maximize the quantity of plastic collected over time. We formulate the problem as a longest path problem in a well-structured graph. However, since collection directly impacts future plastic density, the corresponding edge lengths are non-linear polynomials. After analyzing the structural properties of the edge lengths, we propose a search-and bound method, which leverages a relaxation of the problem solvable via dynamic programming and clustering, to efficiently find high-quality solutions (within 6%-optimal in practice), and develop a tailored branch-and-bound strategy to solve it to provable optimality. On one-year of ocean data, our optimization-based routing approach increases the quantity of plastic collected by over 60% compared with their current routing strategy, hence speeding up the progress towards plastic-free oceans. Supplemental Material: All supplemental materials, including the code, data, and files required to reproduce the results were reviewed and are available at [https://doi.org/10.1287/opre.2023.0515](https://doi.org/10.1287/opre.2023.0515)

London Business School Research Online (London Business School)
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Gyrotron and Vacuum Electronics Research
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Optimizing the Path Towards Plastic-Free Oceans · London Business School Research Online (London Business School) (2025) | TGRS Research Map | TGRS