关于接种疫苗效益的讨论：铁路调度中的一个例子
人工智能
2007-05-23 v1 神经与进化计算
摘要
铁路时刻表在流量发生小扰动后进行局部重构，寻求最小化总累积延误，是非常困难且受到严格约束的组合优化问题。铁路公司的公共形象与日均延误数量成正比，利润也随之下降！本文描述了一种接种疫苗程序，可大大增强铁路重调度的遗传算法效能。该程序包括围绕基于事先可用问题相关信息构建的预计算解作为初始种群。优化通过调整每趗列车在每个车站的出发和到达时间以及轨道分配来实现。这是通过一种基于排列的遗传算法实现的，该算法依赖一种半贪心调度器逐步通过插入列车来重构时刻表。 presented on various instances of a large real-world case involving around 500 trains and more than 1 million constraints. In terms of competition with commercial mathematical programming tool ILOG CPLEX, it appears that within a large class of instances, excluding trivial instances as well as too difficult ones, and with very few exceptions, a clever initialization turns an encouraging failure into a clear-cut success auguring of substantial financial savings.
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引用
@article{arxiv.cs/0611140,
title = {On the Benefits of Inoculation, an Example in Train Scheduling},
author = {Yann Semet and Marc Schoenauer},
journal= {arXiv preprint arXiv:cs/0611140},
year = {2007}
}