A unified operation decision model for dry bulk shipping fleet: ship scheduling, routing, and sailing speed optimization

Dry bulk shipping plays a crucial role in the global transportation of raw material across continents. As the primary player in the dry bulk shipping market, the dry bulk shipping company operates a fleet of vessels to generate revenue by meeting the transportation demands of shippers. The main challenge faced by dry bulk shipping companies is scheduling vessels, optimizing shipping routes, and determining sailing speeds to maximize operational revenue (i.e., the gap between freight revenue and operational costs). To address this problem, we develop an extended space-time network that encompasses collaborative ship scheduling, routing, and sailing speed decisions. We formulate the research problem as a mixed-integer programming model that aims at maximizing the total fleet operation revenue during the planning horizon while satisfying operational constraints. We conduct a series of numerical experiments using an illustrative example and a real-world grain transportation network to validate the effectiveness of our approach. Numerical results demonstrate that our approach is promising and can provide useful insights for dry bulk shipping operations management.