Cost Optimisation to determine ship maintenance schedules for improved operational availability

Abstract

Complex port maintenance operations face significant challenges due to the dynamic nature of port resource availability, variable task urgency, and downtimes having different priorities. This study proposes a dynamic scheduling approach for ship maintenance that integrates agent-based modelling with multi-objective optimisation. By optimising port resource allocation and reducing ship idle costs, the approach significantly enhances operational efficiency in maritime logistics. Utilising a hybrid simulation-optimisation framework, the proposed method adapts downtime priorities and resource allocations rules arising due to classes of ship and their compatibility with the port resources, and their downtimes. Agent-based modelling simulates interactions between ships, port assets, and maintenance activities while Discrete Event Simulation captures the stages of maintenance process. The model re-evaluates the ship maintenance schedules and facility resource downtime schedules to minimise idle time and maximise efficiency. Comparative analyses reveal improvements over static methods, including an average 45% reduction in idle costs of ship due to unavailable resources, with marginal changes in maintenance costs. This approach not only enhances port operational efficiency but also reduces costs associated with ship waiting times, demonstrating its potential application to other complex industrial scheduling problems requiring adaptive solutions.