A dynamic berth allocation model with variable vessel service priorities is proposed to minimize the total handling vessel time in terminal. The First Comes First Served (FCFS) rule is not considered to improve the objective value in the model. A genetic algorithm is improved for the hard model with a reduced basic search space by considering approximate optimal solution properties. A large amount of computational experiments shows that the formulation and the proposed algorithm are adaptable to practical applications.
Over the past several years, port charges in major international hub ports have been increasingly high. One of the reasons for this is a relative decrease in handling volume compared to the terminal capacity by its lease management, resulting in inefficient use of the existing capacity. The use of the Multi-User container Terminal (MUT) concept employed in some of the major container hub ports such as Hong Kong, Singapore reduces redundant terminal space and results in substantial cost saving in cargo handling costs. Meanwhile, most container terminals in china are managed as the MUT model, since the limited terminal space has to be utilized efficiently in order to meet huge container traffic. One of the issues that affect the efficiency of MUT operations is berth allocation for calling vessels to determine their berthing times and positions of containerships.
Throughout the years, many studies have been conducted related to berth allocation subject. Considering first-comes-first-served (FCFS) allocation strategy, Lai and Shih (1992) propose a heuristic algorithm for berth allocation. They identify the optimal set of ship-to-berth assignments that maximizes the sum of benefits for ships while in port. Imai et al. (1997) propose a solution technique for the so-called static berth allocation problem (SBAP).
