Digitised Dockyard: A Digital Twin for Multi-Objective Optimisation

ORCID

Abstract

Digital twin technology is emerging as a transformative tool across multiple industries to digitally represent physical entities for monitoring and simulation. While many implementations focus on single systems or commercial applications, this thesis investigates the use of a digital twin to represent and optimise the operational logistics of a non-commercial, high-security maritime site. By treating the entire base as a holistic entity composed of interdependent systems, such as buildings, utilities, communications infrastructure, personnel, and services, the research explores how artificial intelligence techniques can be embedded within a digital twin to support decision-making.This thesis proposes and develops a bespoke digital twin framework that integrates multi-objective optimisation to address conflicting priorities across multiple layers of the site. Two distinct logistical problems are modelled to demonstrate this approach: the Ships Alongside Services problem and the Space Utilisation problem. Both are formulated as optimisation challenges and solved using single- and multi-objective algorithms within the digital twin. These case studies show how different problem types—graph theory based and spatial allocation—can be integrated into a unified architecture, highlighting the versatility of the proposed system.The research adopts an interdisciplinary methodology that combines principles from computational intelligence, operations research, human–computer interaction, and maritime defence logistics. It contributes novel insights by adapting digital twin technologies to the under-explored context of defence infrastructure and applying optimisation not just for efficiency but for resilience and adaptability in secure, high-stakes environments. A key innovation is the development of a system that enables decision-makers, including non-technical stakeholders, to interact with complex trade-offs through intuitive visual outputs and scenario exploration tools.In doing so, this thesis addresses key research gaps in the literature: the lack of digital twin frameworks for maritime defence applications; the limited integration of multi-objective optimisation techniques within real-world digital twins; and the absence of user-centric design for defence-specific planning tools. The work concludes by outlining a roadmap for future research, including the expansion of use cases, integration of live data through the Internet of Things, and exploration of immersive interfaces such as augmented and virtual reality.

Awarding Institution(s)

University of Plymouth

Award Sponsors

Royal Navy

Supervisor

Kevin Jones, Kimberly Tam, David Walker

Document Type

Thesis

Publication Date

2025

Embargo Period

2026-10-07

Deposit Date

October 2025

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

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This item is under embargo until 07 October 2026

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