An Optimization Model for Supporting Bunkering Decisions in Bulk Shipping

Abstract

This study addresses a bunkering optimization problem for bulk shipping carriers that explores route deviation to find optimal bunkering locations and amounts. A mixed integer linear programming (MILP) model is developed to determine optimal bunkering decisions that minimize total operating costs, including total daily operating costs, bunkering costs, port charges and surcharges, while observing time window constraints at loading/unloading ports. The proposed model is evaluated using instances generated from real data provided by H company with its operational headquarters in Taipei, Taiwan, which operates a fleet of handysize ships in East and South Asia. The results indicate that optimization models incorporating route deviation for bunkering purposes yield superior cost performance to those that restrict ships to bunkering at loading/unloading ports. This study provides a valuable reference point for bulk shipping companies in making bunkering decisions, and hence contributes to both the literature and the practice of bulk shipping.