Quay crane assignment in container terminals using a genetic algorithm

Ports are essential for international trade, connecting production areas to consumer markets. However, port operations often face delays, disrupting supply chains and increasing transit times. To address this, mathematical modeling, particularly through genetic algorithms, offers a solution for optimizing processes like container unloading. This paper presents a model predicting and optimizing unloading times by considering factors such as crane types, schedules, and environmental conditions. Focusing on the Casablanca port, the model addresses scheduling for two gantry and two mobile cranes, treating each bay as a unique task handled by one crane type to avoid conflicts. Using genetic algorithms, the goal is to create efficient schedules that minimize waiting times and maximize crane utilization. The expected outcome is a detailed timetable enabling effective gantry crane use or simultaneous multi-crane operations, enhancing unloading efficiency. This approach can be adapted to other ports with similar challenges, highlighting the model's broader applicability.