The Survival of the Fittest Route: Genetic Algorithms in Shipping and Sustainability
The Turing PodcastShow Notes
How can the study of ant colonies and evolutionary theory help us ensure the resilience and sustainability of global shipping? In this episode, host Amelia Jabry is joined by Professor Adam Sobey (Mission Director for Sustainability at the Alan Turing Institute) and Senior Applied Scientist Dr. Przemyslaw (Slaw) Grudniewski from Theyr. Together, they explore the ‘evolution’ of shipping route optimisation - from early concepts proposed by Alan Turing to cutting-edge Multi-Objective Genetic Algorithms. Discover how these ‘survival of the fittest’ models are being used to navigate the complex world of charter party agreements, fuel efficiency, and autonomous vessels. They also dive into the environmental impact of rerouting, discussing how a 1% change in fuel consumption can protect vital megafauna like whales, and what the melting Arctic means for the future of global trade.
Chapter Markers 0:30 | Co-Host Introduction: Professor Adam Sobey
Introduction of Adam Sobey, Mission Director for Sustainability at the Alan Turing Institute and Professor at the University of Southampton.
1:20 | Guest Introduction: Dr. Przemyslaw (Slaw) Grudniewski
Introduction of Slava, Senior Applied Scientist atTheyr The history of Adam and Slava’s collaboration, starting from Slava's PhD in 2015.
4:30 | The Path to Genetic Algorithms
Why the team focused on genetic algorithms, including the influence of a talk at the University of Bristol on co-evolution mechanisms.
5:00 | Why Shipping Matters: The Ever Given Incident
The significance of global trade by sea (80-90%) and the 2021 Suez Canal blockage by theEver Given.
6:20 | The Sustainability Imperative
Shipping currently accounts for 2-3% of world emissions, emphasizing the massive need for reduced costs and improved sustainability.
7:15 | Defining Genetic Algorithms
Explaining unsupervised learning algorithms based on "survival of the fittest" and evolutionary mechanics.
8:40 | Applying Evolutionary Principles to Route Optimisation
How routes are treated as individuals that create "offspring" through crossover and mutation.
10:20 | Multi-Objective Genetic Algorithms
"There is no one best route"—balancing conflicting goals like voyage time vs. fuel consumption. Explaining why multi-objective approaches provide a set of optimal solutions rather than a single answer.
11:00 | Charter Party Agreements & Alternative Fuels
The complexity of "rental agreements" (charter parties) and the shift toward net-zero fuels like ammonia, hydrogen, and nuclear.
12:20 | The Rise of Fully Autonomous Vessels
Navigating the challenges of crewless ships and how they allow for real-time route adjustments.
13:30 | Sustainability Benefits of Autonomy
Removing crew-related weight can lead to estimated fuel reductions of around 20%.
14:40 | Safety and Regulation
The role of the Alan Turing Institute and Lloyd’s Register in developing standards and validation for autonomous systems.
16:15 | Risks: Cyber Threats and Bad Actors
Addressing piracy, cybersecurity risks, and the safety of alternative fuel sources.
18:00 | Why Genetic Algorithms Win
Comparing genetic algorithms against local search methods like A* and Dijkstra for complex, real-world problems.
19:00 | Top Performance: cMLSGA
ThecMLSGA (Convolutional Multi-Level Selection Genetic Algorithm) and its 7-8% improvement over other models. This represents a saving of 50 to 380 tonnes of fuel per day for large vessels.
20:20 | History: From Alan Turing to Today
How the field traces back to Turing’s 1948 ideas of "child-like" intelligence that learns and evolves.
22:20 | Ants, Tribes, and Co-Evolution
Using the study of ant colonies and human tribal behaviour to understand collective fitness and reproduction.
23:50 | Scaling Solutions through Collectives
Applying the concept of "collectives" to solve large-scale optimisation problems through collaboration.
25:25 | Multi-Level Selection
How "groups of individuals" (collectives
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