The problem of personnel and interventions scheduling faced by a container ship maintenance service provider (MSPC), commonly the manufacturer of a main ship subsystem such as engines, is analysed. Clients can make a request for a maintenance service of a containership at a given harbour with a given number of days in advance to the desired date, as established in the service contract. The MSPC is allowed to delay the intervention to any future stop of the route within a specified time window depending on its urgency, as set in the contract. The MSPC technicians can be divided into different categories of skills and further distinguished as belonging to the MSPC main company, to the MSP network of subsidiaries, or hired on demand, with different availability constraints, personnel costs, and transport costs in relation to harbour proximity. Delays on planned arrival dates to harbours as well as changes in the duration of stay are common due to bad meteorological conditions, congestions at harbours, or other issues arisen during sailing or previous stops, so a rolling planning horizon should be adopted to face such a dynamic environment.
A Constraint Programming optimisation model hybridized with Large Neighborhood Search is proposed in order to address the problem and its performance compared to actual plans from a world-wide known MSPC. The model has been developed to perform also as a decision making tool; a factorial design of experiment is adopted in order to analyse the impact of a change in some contractual features, such as the minimum time allowed to clients for requiring a service, or the maximum delay allowed to the MSPC to satisfy a service request. How granting clients more flexibility while preserving efficacy and efficiency of the service can so be investigated.
