Black-box simulation-based optimization for berth allocation in multipurpose ports: a case study in Colombia

Abstract

Purpose: This study aims to optimize berth allocation at a multipurpose terminal on the Magdalena River in Colombia. By addressing the berth allocation problem (BAP) while considering key constraints such as berth capacity, vessel specifications, cargo diversity and fluctuating operational demands, the goal is to significantly enhance efficiency, increase revenue and improve service quality. Design/methodology/approach: The research adopts a three-phase methodology: (1) standardization and characterization of vessel operations, (2) development of a dynamic simulation model to replicate terminal activities and (3) application of simulation-based optimization techniques. This iterative process integrates simulation with optimization algorithms to enhance terminal performance by optimizing revenue, reducing waiting times and balancing operational factors. Findings: The study resulted in a 6.22% revenue increase, reduced ship diversions and improved adaptability to waiting times. By employing black-box simulation-based optimization, the research demonstrates the critical role of data-driven approaches in enhancing port management efficiency. Originality/value: This study makes a valuable contribution by applying black-box simulation-based optimization in a real-world port setting. It provides actionable insights into port operations and logistics, showcasing the power of advanced optimization algorithms in addressing complex logistical challenges, with significant implications for both academic research and practical port management applications.