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Model and algorithm for resolving regional bus scheduling problems with fuzzy travel times

机译:解决具有模糊行驶时间的区域公交车调度问题的模型和算法

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Regional bus scheduling is necessary to urban public transport that is complicated by the necessity of assigning trips that belong to several routes to buses located at different depots while reducing fleet size and operating costs. Considering the reality of emergencies that may interfere with the ability of vehicles to complete trips on time, it is reasonable to use fuzzy numbers to express uncertain delay times. Based on this idea, this paper proposes a chance-constrained programming model of regional bus scheduling that will reflect additional constraints such as the capacities of related depots and fueling needs. The objective of this paper is to maximize utilization of fleet vehicles. To overcome the defect of premature convergence in the particle swarm optimization algorithm (PSO), an improved PSO is proposed by using an organic fusion with group search optimization. Finally, an example demonstrates the correctness and effectiveness of the model and algorithm.
机译:对于城市公共交通来说,区域公交车调度是必不可少的,因为必须将属于多条路线的出行分配给位于不同仓库的公交车,同时还要减少车队规模和运营成本。考虑到可能会干扰车辆按时完成行程的紧急情况,使用模糊数字表示不确定的延迟时间是合理的。基于此思想,本文提出了区域公交车调度的机会受限编程模型,该模型将反映其他约束,例如相关车厂的容量和加油需求。本文的目的是最大程度地利用车队车辆。为了克服粒子群优化算法(PSO)中过早收敛的缺陷,提出了一种有机融合与群体搜索优化相结合的改进粒子群算法。最后,通过一个例子说明了该模型和算法的正确性和有效性。

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