关键词: 低碳经济, 泊位分配, 遗传算法, 可变的到港时间（VAT）策略

Abstract: Shipping companies are making an unprecedented effort to reduce fuel consumption and carbon emissions during the voyage, which are directly effected by port’s berth allocation plan. Considering the ship’s arrival time is a key parameter in the formulation of berth allocation plan for ports, this paper introduces the ship’s arrival time into the traditional BAP（Berth Allocation Problem） model as a decision variable, designs a new berth allocation strategy—VAT（Variable Arrival Time） strategy, which is based on the coordination between the ports and the ship operators, blends the fuel consumption and carbon emission in the BAP model’s target function and builds bi-objective（minimizing fuel consumption and departure delay time） optimization model, uses MOGA（Multi-Objective Genetic Algorithms） to solve the model and validates the strategy by a simulation example. The calculation indicates that VAT strategy can reduce shipping companies’ fuel consumption and carbon emission greatly. At the same time, it can also improve the service level of the ports and cut down the waiting time of the ships.

Key words: low-carbon economy, berth allocation plan, genetic algorithm, Variable Arrival Time（VAT） strategy