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考虑在实际运营中乘客需求具有随机性,固定需求下优化的公交时刻表不适应运营的要求.随机需求下的期望值模型忽略了不利可能事件对运营的负面影响,针对此情况研究随机需求下公交时刻表设计的鲁棒性优化.模型综合考虑乘客成本与运营成本,采用鲁棒性优化权衡目标期望值与偏差期望值.结合随机模拟技术,选用遗传算法求解模型.给出了算例,验证了模型和算法的有效性.通过比较固定需求模型、随机需求期望值模型、随机需求鲁棒性模型,说明在鲁棒性优化下需要提供更多的交通供给以降低偏差期望值.最后,对鲁棒性模型中的偏差权重系数进行了灵敏度分析.
Considering the randomness of passenger demand in actual operation, the bus schedule optimized under fixed demand does not meet the requirements of operation.The expected value model under random demand ignores the negative impact of adverse events on operations, and in this case, Robust optimization of schedule design.Considering the passenger cost and operating cost, the model uses the robust optimization to weigh the target expectation and deviation expectation.Combined with stochastic simulation technology, the genetic algorithm is used to solve the model.An example is given to verify the model And the effectiveness of the algorithm.Through the comparison of the fixed demand model, the random demand expectation model and the stochastic demand robustness model, it is necessary to provide more traffic supplies to reduce the expected deviation under the robust optimization.Finally, the robustness model In the deviation of the weight coefficient sensitivity analysis.