公益性物流发展策略研究

物流业作为国民经济和社会发展的基础性、战略性产业,以"市场运作,政府引导"为主要原则的发展模式,极大地发挥了市场在物流发展中的决定性作用,较好地解决了政府与市场的关系问题。然而,物流不仅具有经济性,同时还具有社会性,以国有资本发展公益性物流是政府保持宏观经济稳定,加强和优化公共服务,保障公平竞争,推动可持续发展,促进共同富裕,弥补市场失灵的重要政策方向。     

Observed and simulated traffic impacts from the 2013 Bay Area Rapid Transit strike

Despite high costs, many cities build public transit to address regional equity, environmental and economic goals. Although public transit accounts for a minority of trips (～5%), the impact is widely felt when service is suspended during a strike through excess road demand and slower journeys. In 2013, Bay Area Rapid Transit (BART) workers participated in two brief strikes, and the resulting traffic conditions illustrate the value of transit to drivers in the San Francisco Bay Area region. This paper tests the impact of rail transit service interruption on freeway traffic conditions using volumes and travel times. During the strike, regional freeway conditions showed negligible change. However, on facilities that parallel BART service, the impacts are as bad as the worst day of a typical week. Conditions on the San Francisco–Oakland Bay Bridge showed significant impacts with travel times and volumes nearly doubling the baseline median values on the worst day.     

Solving the K-shortest paths problem in timetable-based public transportation systems

Finding the K-shortest paths in timetable-based public transportation systems is an important problem in practice. It has three typical variants: the K-earliest arrival problem (K-EAP), the K-shortest travel time problem (K-STTP), and the K-minimum number of transfers problem (K-MNTP). In this article we show that these problems can be solved efficiently by first modeling the timetable information with the time-expanded approach, then applying the Martins and Santos (MS) algorithm. Then we model the timetable information with the time-dependent approach and propose a modified version of the MS algorithm for solving the K-EAP. Experimental results on real-world data show that for K smaller than 100, which is enough for most applications, the execution times of the MS algorithm for the problems in the time-expanded model are less than 100 ms on a server with a 1.86-GHz central processing unit (CPU) and 4 GB of memory. For solving the K-EAP the modified MS algorithm in the time-dependent model is even more efficient (about three times faster for K ≤ 100) than the original algorithm in the time-expanded model. Our results imply the great potential of the MS algorithms in practical transportation service systems.     

人工智能在镇江公交成本控制中的应用研究

近年来,人工智能技术发展迅速,并被广泛应用于不同行业.在公交行业运用人工智能技术进行成本控制,可以使得成本数据核算和分析更加准确,从而提升企业成本管控水平,提高乘客的服务满意度,提升企业的市场竞争力.作为公交企业,镇江公交承担着一定的社会责任,导致其无法通过提高客票收入来缓解经营成本压力.本文以镇江公交为研究对象,从该...