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采用数学规划的方法从静力和动力两方面对斜腿刚构桥的几何布局进行优化设计。静力优化设计的优化目标是截面截面应力平方均值最小,动力优化设计的优化目标是结构自振周期平方和最小。采用了直接搜索法寻优。通过算例可知,这两种优化设计方法均可行,且均为刚性设计。 相似文献
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上海市杨浦区某些街坊小区一遇暴雨即产生严重的积水问题。通过调查研究,找出病症,提出改造方案.有效地解决了小区的积水顽症。本文结合实际,总结了若干综合技术措施和行政管理、协调手段。 相似文献
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基于红外搜索系统的被动测距技术研究 总被引:1,自引:0,他引:1
红外搜索系统是一种被动探测系统,量测数据中无目标的距离量;而评判来袭目标的威胁程度离不开其距离量。介绍了基于红外搜索系统的被动测距技术测量目标距离的算法、原理框图以及仿真试验与结果。 相似文献
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根据摘挂列车编组调车作业原理,将摘挂列车下落问题抽象为排序问题,提出一种基于排序二叉树的编组钩计划自动编制方法.根据待编列车序列构造排序二叉树;利用排序二叉树的有序性快速搜索出有序车组序列,将其作为下落方案的可选集.考虑邻组、暂合列内收编固定组组别和空闲组别、端组等因素,从可选集中筛选出较优的下落方案.通过定义收编固定组简化列车收编过程,实现列车收编过程的计算机自动编制.通过实例验证,采用该方法降低了选择下落方案的复杂性,减少了列车编组钩计划的调车钩数,而且可根据实际调车线数灵活调整方案. 相似文献
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邮政车辆调度问题及其优化算法 总被引:1,自引:0,他引:1
从邮政实际运营情况出发,在兼顾其他限制条件的同时,着重研究带路程长度和装载能力限制的邮车调度问题,抽象出此类问题的数学模型,并设计一个禁忌搜索算法进行求解。算例测试结果表明,采用该算法可以在很短的时间内求出较高质量的邮车调度问题的优化解。 相似文献
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The use of smartphone technology is increasingly considered a state-of-the-art practice in travel data collection. Researchers have investigated various methods to automatically predict trip characteristics based upon locational and other smartphone sensing data. Of the trip characteristics being studied, trip purpose prediction has received relatively less attention. This research develops trip purpose prediction models based upon online location-based search and discovery services (specifically, Google Places API) and a limited set of trip data that are usually available upon the completion of the trip. The models have the potential to be integrated with smartphone technology to produce real-time trip purpose prediction. We use a recent, large-scale travel behavior survey that is augmented by downloaded Google Places information on each trip destination to develop and validate the models. Two statistical and machine learning prediction approaches are used, including nested logit and random forest methods. Both sets of models show that Google Places information is a useful predictor of trip purpose in situations where activity- and person-related information is uncollectable, missing, or unreliable. Even when activity- and person-related information is available, incorporating Google Places information provides incremental improvements in trip purpose prediction. 相似文献
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Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFBS depends on the efficiency of its rebalancing operations to serve the maximal demand as possible.Bicycle rebalancing refers to the reestablishment of the number of bikes at sites to desired quantities by using a fleet of vehicles transporting the bicycles. Static rebalancing for SBBS is a challenging combinatorial optimization problem. FFBS takes it a step further, with an increase in the scale of the problem. This article is the first effort in a series of studies of FFBS planning and management, tackling static rebalancing with single and multiple vehicles. We present a Novel Mixed Integer Linear Program for solving the Static Complete Rebalancing Problem. The proposed formulation, can not only handle single as well as multiple vehicles, but also allows for multiple visits to a node by the same vehicle. We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which is both effective and efficient in solving static complete rebalancing problems for large-scale bike sharing programs.Computational experiments were carried out on the 1 Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP) instances used previously in the literature and on three new sets of instances, two (one real-life and one general) based on Share-A-Bull Bikes (SABB) FFBS program recently launched at the Tampa campus of University of South Florida and the other based on Divvy SBBS in Chicago. Computational experiments on the 1-PDTSP instances demonstrate that the proposed algorithm outperforms a tabu search algorithm and is highly competitive with exact algorithms previously reported in the literature for solving static rebalancing problems in SBSS. Computational experiments on the SABB and Divvy instances, demonstrate that the proposed algorithm is able to deal with the increase in scale of the static rebalancing problem pertaining to both FFBS and SBBS, while deriving high-quality solutions in a reasonable amount of CPU time. 相似文献