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The durability of geosynthetics is important for their service life, transportation and long-term storage.
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In real-life transportation, time windows may be violated due to several reasons as given in Tang et al. (2009).
The vehicle routing in real-life transportation, distribution and logistics may change with time, especially when there is existing technology that can produce real-time routing data.
This work integrates the use of transportation modeling with mathematical programming for the solution of a complex large-scale problem on a real-life transportation network.
This paper is focused on calibration of an intelligent network simulation model (INSIM) with real-life transportation network to analyse the INSIM's feasibility in simulating commuters' travel choice behaviour under the influence of real-time integrated multimodal traveller information (IMTI).
We first developed a mathematical framework to compute the coverage in a multiplex network setting, which we applied to different synthetic and real-life transportation systems built from four different cities, namely Chicago, London, New York, and Paris.
This problem is strongly connected to real-life transportation systems where the packing of items to be delivered by each vehicle can have a significant impact on the routes.
Validation criteria such as specificity, detection limit, accuracy, reproducibility and storage conditions were assessed using reference plasma samples prepared as DPS and clinical DSS from the German molecular HIV-1 surveillance processed under real-life transportation conditions.
Accidents, bad weather, traffic congestion, etc. contribute to the uncertainties of travel times in real-life transportation networks, which greatly affect the quality of individual life and the reliability of transportation system.
Driving the National Road is an exercise in trying to recreate a time when life, and transportation, moved much more slowly.
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