Notice of Retraction: An optimal routing strategy based on random-walk betweenness

Author(s):  
Fei Shao
2011 ◽  
Vol 60 (11) ◽  
pp. 118903
Author(s):  
Wang Kai ◽  
Zhou Si-Yuan ◽  
Zhang Yi-Feng ◽  
Pei Wen-Jiang ◽  
Liu Qian

2021 ◽  
Author(s):  
Linh Nguyen

<pre>The paper addresses the problem of efficiently planning routes for multiple ground vehicles used in goods delivery services. Given popularity of today's e-commerce, particularly under the COVID-19 pandemic conditions, goods delivery services have been booming than ever, dominated by small-scaled (electric) bikes and promised by autonomous vehicles. However, finding optimal routing paths for multiple delivery vehicles operating simultaneously in order to minimize transportation cost is a fundamental but challenging problem. In this paper, it is first proposed to exploit the mixed integer programming paradigm to model the delivery routing optimization problem (DROP) for multiple simultaneously-operating vehicles given their energy constraints. The routing optimization problem is then solved by the multi-chromosome genetic algorithm, where the number of delivery vehicles can be optimized. The proposed approach was evaluated in a real-world experiment in which goods were expected to be delivered from a depot to 26 suburb locations in Canberra, Australia. The obtained results demonstrate effectiveness of the proposed algorithm.</pre>


2015 ◽  
Vol 29 (25) ◽  
pp. 1550149
Author(s):  
Zhanli Zhang

Coupling entropy of co-processing model on social networks is investigated in this paper. As one crucial factor to determine the processing ability of nodes, the information flow with potential time lag is modeled by co-processing diffusion which couples the continuous time processing and the discrete diffusing dynamics. Exact results on master equation and stationary state are achieved to disclose the formation. In order to understand the evolution of the co-processing and design the optimal routing strategy according to the maximal entropic diffusion on networks, we propose the coupling entropy comprehending the structural characteristics and information propagation on social network. Based on the analysis of the co-processing model, we analyze the coupling impact of the structural factor and information propagating factor on the coupling entropy, where the analytical results fit well with the numerical ones on scale-free social networks.


2014 ◽  
Vol 25 (09) ◽  
pp. 1450044 ◽  
Author(s):  
Zhong-Yuan Jiang

The link congestion based traffic model can more accurately reveal the traffic dynamics of many real complex networks such as the Internet, and heuristically optimizing each link's weight for the shortest path routing strategy can strongly improve the traffic capacity of network. In this work, we propose an optimal routing strategy in which the weight of each link is regulated incrementally to enhance the network traffic capacity by minimizing the maximum link betweenness of any link in the network. We also estimate more suitable value of the tunable parameter β for the efficient routing strategy under the link congestion based traffic model. The traffic load of network can be significantly balanced at the expense of increasing a bit average path length or average traffic load.


2020 ◽  
Vol 12 (2) ◽  
pp. 714 ◽  
Author(s):  
Jooyoung Kim

Demand responsive transport (DRT) is operated according to flexible routes, dispatch intervals, and dynamic demand, is attracting a lot of attention. The biggest characteristic of the DRT service is that the vehicle routes and schedules are operated optimally based on real-time travel requests of using passengers without fixed operating schedules. This study analyzed the feasibility of implementing the DRT service by analyzing the benefits for the users and cost of the operator from the effects of increasing public transportation use and providing personalized mobility service based on DRT implementation by the introduction of DRT using multi-agent transport simulation (MATSim). Through the simulation, the DRT is expected to provide convenient, fast, and cost-effective mobility services to customers; provide an optimal vehicle scale to providers; and, ultimately, achieve a safe and efficient transportation system.


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