Dynamic syncrolift dock scheduling

Dry-docking plays a crucial role in the overall maintenance process of ships, enabling maintenance, repair, and inspection operations to be carried out without the constraints of being in the water and allowing merchant ships to renew their safety certificates. As the global merchant fleet continues to grow, the need for regular dry-docking services is also increasing. In response to these pressing needs, the operational efficiency of dry docks, the specialized facilities for these services, has become crucial. This study addresses this challenge by formulating a dynamic scheduling problem for a syncrolift dock, a modern dry-dock facility featuring a lifting platform, a rail-based transfer system, and multiple onshore berths. The proposed model accounts for the dynamic arrival of ships and incorporates time-dependent nature of ship arrival time uncertainty, reflecting the real-world phenomenon that uncertainty diminishes as actual arrival approaches. To generate the dynamic scheduling for the syncrolift dock, we propose an efficient rolling-horizon decision framework. At each decision epoch, this framework iteratively produces an immediate operational plan by solving a robust subproblem aimed at minimizing the worst-case total departure delay cost of ships based on the time-dependent arrival time uncertainty. Each robust subproblem is solved using a column-and-constraint generation (C&CG) method, whose performance is further enhanced by incorporating a novel cycle-and-path-based iterative method for the master problem and utilizing a dedicated network flow formulation for the subproblem. Extensive computational experiments demonstrate the effectiveness of the proposed methodology and provide practical insights for enhancing the operational management of syncrolift dock facilities.