A new model for multi-port berth allocation problem based on an improved genetic algorithm

Port integration can enhance operational efficiency and service level in response to heightened competition among container ports. Nevertheless, container ports are still considered independent systems separately in formulating scheduling plans. This research explores a new multi-port berth allocation problem (MPBAP) with continuous berth layout considering the mutual influence between ports. The MPBAP is compared with the single port berth allocation, and effects of different numbers of vessels continuously berthing at all ports on a single route on the MPBAP are discussed through vessel operation rate. The problem is formulated by a mixed integer programming model by minimising the total port stay time of all vessels. The quay is highly discretised and a GA coupled with parallel computing is applied to accelerate the search for the optimal model solution. A case study is conducted on two adjacent container ports located along the Yangtze River. Results show that multi-port coordinated scheduling is efficiency and the total port stay time of all vessels reduces by an average of 2.63% under the MPBAP. With more than four vessels berthing continuously at two ports on a single route, the MPBAP shows a higher vessel operation rate and the rate gap between the two models exceeds 2%. The approach suggested in this study can enhance the port system's efficiency and provide a new idea for coordinated scheduling in other port groups.