Berth Allocation Considering Multiple Quays: A Practical Approach Using Cuckoo Search Optimization

Maritime container terminals (MCTs) play a fundamental role in international maritime trade, handling inbound, outbound, and transshipped containers. The increasing number of ships containers creates several challenges to MCTs, such as congestion, long waiting times before dock, delayed departures, high service costs. berth allocation problem (BAP) concerns allocating berthing positions arriving reduce total cost, times, delays vessels’ departures. In this work, we extend the study continuous BAP, which considers single quay (straight line) for ships, multiple quays, found many ports around globe. Multi-Quay BAP (MQ-BAP) adds additional dimension assigning preferred each ship, rather than just specifying position time. study, address MQ-BAP with objective minimizing includes departure ships. is first formulated mixed-integer linear then solved using cuckoo search algorithm (CSA), computational intelligence (CI)-based approach. addition, exact programming (MILP) method, two other state-of-the-art metaheuristic approaches, namely genetic (GA) particle swarm optimization (PSO), well come serve (FCFS) approach, are also implemented comparison purposes. Several experiments conducted both randomly generated real data from Port Limassol, Cyprus, has five quays serving commercial vessel traffic. comparative analysis experimental results show that CSA-based method achieves best overall affordable time compared CI-based methods, all considered scenarios.