A pro-active real-time control approach for dynamic vehicle routing problems dealing with the delivery of urgent goods

2013 ◽  
Vol 225 (1) ◽  
pp. 130-141 ◽  
Author(s):  
Francesco Ferrucci ◽  
Stefan Bock ◽  
Michel Gendreau
2003 ◽  
Vol 1857 (1) ◽  
pp. 102-108 ◽  
Author(s):  
Ta-Yin Hu ◽  
Tsai-Yun Liao ◽  
Ying-Chih Lu

Recent advances in commercial vehicle operations (CVO), especially in communication and information technologies, allow the study of dynamic vehicle routing problems under new and updated information, such as traffic conditions and new customers. Two major operational benefits of CVO include ( a) dynamically assigning vehicles to time-sensitive demands, and ( b) efficiently rerouting vehicles according to current traffic conditions. In this research, stochastic vehicle routing problems (SVRP) are considered and extended to incorporate real-time information for dynamic vehicle routing problems. The SVRP model is formulated by a chance-constrained model and is solved by CPLEX with branch-and-bound techniques. Numerical experiments are conducted in a Taichung city network to investigate dynamic vehicle routing strategies under real-time information supply strategies and to assess the effectiveness of such strategies in a dynamic perspective.


2021 ◽  
pp. 107604
Author(s):  
Brenner Humberto Ojeda Rios ◽  
Eduardo C. Xavier ◽  
Flávio K. Miyazawa ◽  
Pedro Amorim ◽  
Eduardo Curcio ◽  
...  

2015 ◽  
Vol 76 (5) ◽  
pp. 935-943 ◽  
Author(s):  
V. V. Zakharov ◽  
A. N. Shchegryaev

2014 ◽  
pp. 299-347 ◽  
Author(s):  
Tolga Bekta¸s ◽  
Panagiotis P. Repoussis ◽  
Christos D. Tarantilis

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2842
Author(s):  
Mario Maiolo ◽  
Stefania Anna Palermo ◽  
Anna Chiara Brusco ◽  
Behrouz Pirouz ◽  
Michele Turco ◽  
...  

The real-time control (RTC) system is a valid and cost-effective solution for urban stormwater management. This paper aims to evaluate the beneficial effect on urban flooding risk mitigation produced by applying RTC techniques to an urban drainage network by considering different control configuration scenarios. To achieve the aim, a distributed real-time system, validated in previous studies, was considered. This approach uses a smart moveable gates system, controlled by software agents, managed by a swarm intelligence algorithm. By running the different scenarios by a customized version of the Storm Water Management Model (SWMM), the findings obtained show a redistribution of conduits filling degrees, exploiting the whole system storage capacity, with a significant reduction of node flooding and total flood volume.


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