An Improved d-MP Algorithm for Reliability of Logistics Delivery Considering Speed Limit of Different Roads

Signals Pub Date : 2022-12-13 DOI:10.3390/signals3040053
W. Yeh, Chia-Ling Huang, Haw-Sheng Wu
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Abstract

The construction of intelligent logistics by intelligent wireless sensing is a modern trend. Hence, this study uses the multistate flow network (MFN) to explore the actual environment of logistics delivery and to consider the different types of transportation routes available for logistics trucks in today’s practical environment, which have been neglected in previous studies. Two road types, namely highways and slow roads, with different speed limits are explored. The speed of the truck is fast on the highway, so the completion time of the single delivery is, of course, fast. However, it is also because of its high speed that it is subject to many other conditions. For example, if the turning angle of the truck is too large, there will be a risk of the truck overturning, which is a quite serious and important problem that must be included as a constraint. Moreover, highways limit the weight of trucks, so this limit is also included as a constraint. On the other hand, if the truck is driving on a slow road, where its speed is much slower than that of a highway, it is not limited by the turning angle. Nevertheless, regarding the weight capacity of trucks, although the same type of trucks running on slow roads can carry a weight capacity that is higher than the load weight limit of driving on the highway, slow roads also have a load weight limit. In addition to a truck’s aforementioned turning angle and load weight capacity, in today’s logistics delivery, time efficiency is extremely important, so the delivery completion time is also included as a constraint. Therefore, this study uses the improved d-MP method to study the reliability of logistics delivery in trucks driving on two types of roads under constraints to help enhance the construction of intelligent logistics with intelligent wireless sensing. An illustrative example in an actual environment is introduced.
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考虑不同道路限速的物流配送可靠性改进d-MP算法
利用智能无线传感构建智能物流是一种现代趋势。因此,本研究使用多状态流网络(MFN)来探索物流配送的实际环境,并考虑物流卡车在当今实际环境中可使用的不同类型的运输路线,这些在以前的研究中被忽视了。探讨了两种不同限速的道路类型,即高速公路和慢速道路。卡车在高速公路上的速度很快,所以单次交付的完成时间当然很快。然而,也正是因为它的高速,它受到许多其他条件的影响。例如,如果卡车的转向角太大,就会有卡车倾覆的风险,这是一个非常严重和重要的问题,必须作为约束条件。此外,高速公路限制了卡车的重量,因此这一限制也被视为一种限制。另一方面,如果卡车在慢速道路上行驶,其速度比高速公路慢得多,则不受转弯角度的限制。然而,关于卡车的承载能力,尽管在慢速道路上行驶的相同类型的卡车可以承载比在高速公路上行驶的负载重量限制更高的重量能力,但是慢速道路也有负载重量限制。除了卡车前面提到的转弯角度和装载重量外,在当今的物流配送中,时间效率极其重要,因此配送完成时间也受到限制。因此,本研究采用改进的d-MP方法研究了约束条件下卡车在两种道路上行驶的物流配送可靠性,以帮助加强智能无线传感的智能物流建设。介绍了一个实际环境中的示例。
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来源期刊
CiteScore
3.20
自引率
0.00%
发文量
0
审稿时长
11 weeks
期刊最新文献
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