基于PSO算法的海运集装箱超订模型  

Overbooking Model for Ocean Shipping Containers Based on Particle Swarm Optimization

作　　者：白子建[1] 

机构地区：[1]天津大学管理学院,天津300072

出　　处：《河南科学》2010年第3期271-274,共4页Henan Science

基　　金：国家自然科学基金(50908155)

摘　　要：在海运集装箱重箱舱位和空箱舱位同时存在超订的情况下,将集装箱船的运输能力设定为离散型的随机变量,建立了极小化期望总成本的海运集装箱超订模型.模型中假定重箱和空箱的单位舱位超订成本均随着超订水平单调递增.针对最优超订问题设计了粒子群优化(Particle Swarm Optimization,PSO)算法进行求解,并以数值算例表明了该方法的有效性.Considering the overbooking strategies existing in both the full container position and the empty container position, this paper proposes an overbooking model of the ocean shipping container position with the expected total cost as the optimization objective by regarding the uncertain capacity of container position as a discrete random variable. The oversale cost of per container position is assumed to be a monotonically increasing function with respect to overbooking level. The optimal solution of the overbooking model can be solved through Particle Swarm Optimization （PSO）. Finally, example illustrates the effectiveness of the presented method.

关 键 词：集装箱 超订模型 粒子群优化 

分 类 号：O221[理学—运筹学与控制论]