基于遗传算法的集装箱后方堆场箱位分配策略*

根据重庆港实际情况建立了以提箱时间为制约因素，以最小化翻箱率为目标的集装箱后方堆场箱位分配模型，并针对模型提出了基于遗传算法的解决方案。方案对一次卸船或者进港的一批箱进行全局优化，并考虑其分配对后续集装箱的影响。遗传算法迭代过程中采用适应度函数指数变换防早熟，采用可行解替换法处理约束，并设计最优解保存策略保证最终的优化效果。最后针对实际堆场的不同规模，对方案的优化结果同文献中的其他遗传算法方案进行比较,证明了本文优化策略的优越性和实用性。

Location allocation strategy for rear yard based on genetic algorithm

Based on the practice application of Chongqing harbour, proposed a assignment model for container in rear yard firstly, which was limited by time of picking up container and aimed at the minimal container-turned rate. According to the above model, then addressed a genetic algorithm-based solution. A batch of containers were global optimized in the solution,and its effect on follow-up containers was also considered.In iterative process of genetic algorithms, used the fitness function exponential transform to avoid early-mature, used a replacement method to solve constraint, and used a strategy of saving best solution to ensure optimization of the final result.Finally, proved the proposed solution advantage and practicability by comparison with other genetic algorithms to which referred in different actual size of yard.