Optimizing the Path Towards Plastic-Free Oceans

Dick den Hertog (), Jean Pauphilet (), Yannick Pham (), Bruno Sainte-Rose () and Baizhi Song ()
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Dick den Hertog: Amsterdam Business School, University of Amsterdam, 1018 TV Amsterdam, Netherlands
Jean Pauphilet: Management Science and Operations, London Business School, London NW1 4SA, United Kingdom
Yannick Pham: The Ocean Cleanup, 3011 AD Rotterdam, Netherlands
Bruno Sainte-Rose: The Ocean Cleanup, 3011 AD Rotterdam, Netherlands
Baizhi Song: Management Science and Operations, London Business School, London NW1 4SA, United Kingdom

Operations Research, 2025, vol. 73, issue 3, 1165-1183

Abstract: Increasing ocean plastic pollution is irreversibly harming ecosystems and human economic activities. We partner with a nonprofit 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, because collection directly impacts future plastic density, the corresponding edge lengths are nonlinear 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 more than 60% compared with the current routing strategy, hence speeding up the progress toward plastic-free oceans.

Keywords: Environment; Energy; and Sustainability; ocean cleaning; sustainable operations; longest path problem; dynamic programming; branch and bound; polynomial optimization (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:73:y:2025:i:3:p:1165-1183

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