Bulk ship fleet scheduling in industrial shipping for multiple destinations with time-variant loading constraints

Abstract

Bulk carriers are essential in the worldwide transport of raw materials between continents. Most quintessential challenges confronting bulk shipping companies are in regard to the arrangement of ship deployment, voyage assignment, and voyage durations to reduce both operational and capital expenses. To address this issue, a discrete space–time model is designed that integrates fleet sizing and mix, voyage planning, and sailing speed optimization decisions within a cooperative framework in an industrial shipping context. This framework is specifically tailored to industrial shipping with operations involving a single bulk export terminal (BET) and multiple bulk import terminals (BITs) and also takes into account time-dependent handling capability of the BET. The problem is formulated as a mixed-integer programming model, aiming to minimize fleet costs over the planning horizon while adhering to operational constraints and total transport demand. A Lagrangian relaxation-based method was employed to address this problem. Numerical experiments based on a real-world bauxite transportation network demonstrate the validity of the proposed approach. Additionally, sensitivity analyses are conducted to assess the impact of factors such as seasonal variations and unforeseen incidents. The results demonstrate the effectiveness of the method, offering insights for the enhancement of bulk shipping operations management.