基于多目标混沌云粒子群算法的泊位-岸桥分配研究

为了提高集装箱港口泊位-岸桥分配效果和优化效率,以集卡运距和船舶在港时间最小为优化目标,建立了多目标离散泊位-岸桥分配模型,利用混沌云粒子群算法对泊位-岸桥分配模型进行求解,开发了粒子可行-整数化处理模块,内嵌于混沌云粒子群算法进化中,制定了粒子编码规则,设计了多目标函数的粒子历史极值和全局极值的计算方法,提出了基于混沌云粒子群优化算法求解多目标离散泊位-岸桥分配模型的新方法,数值算例结果证明了该模型和算法的可行性和实用性。

Berth and quay-crane allocation based on multi-objective chaos cloud particle swarm optimization algorithm

To improve allocation effectiveness and optimize efficiency of the berth and quay-crane incontainer terminal, a multi-objective berth and quay-crane allocation mode is established, so as to minimize thetransportation distance of container truck and stay time of ships in terminal, and the Chaos Cloud Particle SwarmOptimization (CCPSO) algorithm is used to solve the new model. The feasible-integer processing module for particlesis designed, and embedded in the CCPSO algorithm. Devising the rules of particles encoding and calculation methodof the historical extremum and the global extremum of particles, a new multi-objective berth and quay-craneallocation mode optimized by the CCPSO algorithm is proposed. Numerical example result shows that the proposedmodel and algorithm has certain the practicability and effectiveness.