Reliability-Based Route Optimization of a Transportation Network with Random Arc Capacities and Time Threshold

Author(s):  
Tao Zhang ◽  
Bo Guo ◽  
Yuejin Tan
2021 ◽  
Vol 36 (2) ◽  
pp. 171-178
Author(s):  
Dr. Shilpa C. Shinde ◽  
N. Balasubramanian

Value chains have increased in intricacy and length in recent decades as firms prepare to tackle expanding globalisation with increased peripheral advancements. This involves the adoption of leaner supply chains as well as the formation of ecosystems that provide a stable environment and a constant flow of operations. However, because disruptions are inevitable in today's world, the operational models must be tuned to handle any risks. Complex production networks are designed for a variety of reasons, including cost, proximity to markets, and mass standardisation, but not necessarily for transparency or resilience. Any organization's supply chain operations can be a cause of vulnerability or resilience, depending on its capacity to assess risks, adopt risk mitigation methods, and develop effective business continuity plans. Transportation is the most important component in value chains, and transportation resilience is critical in recovering production networks through precise scheduling and achieving resilience indicators such as lowest trip time, minimum cost, and route optimization, among others. The goal of this research is to clarify the key issues in network restoration scheduling and to offer a unique resilience-based optimization model for post-disaster transportation network restoration, in order to clear up theoretical and empirical ambiguity. Cashew industry which is seasonal as well as face many disruptions in production and processing stages was considered for the study. The study's objectives are (a) Study resilience indexes and its influence on transportation system optimization and (b) Study influence of resilience indexes on industry-based challenges with cashew product. The study objectives were addressed utilising an optimization model based on OR techniques and computer programming. The ideal solution for transportation cost, time, and efficiency can be obtained with the least amount of adjustment and analysis time, allowing cashew farmers to take advantage of transportation resilience and earn financial and environmental benefits.


2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Sun Ji-yang ◽  
Huang Jian-ling ◽  
Chen Yan-yan ◽  
Wei Pan-yi ◽  
Jia Jian-lin

This paper proposes a flexible bus route optimization model for efficient public city transportation systems based on multitarget stations. The model considers passenger demands, vehicle capacities, and transportation network and aims to solve the optimal route, minimizing the vehicles’ running time and the passengers’ travel time. A heuristic algorithm based on a gravity model is introduced to solve this NP-hard optimization problem. Simulation studies verify the effectiveness and practicality of the proposed model and algorithm. The results show that the total number of vehicles needed to complete the service is 17–21, the average travel time of each vehicle is 24.59 minutes, the solving time of 100 sets of data is within 25 seconds, and the average calculation time is 12.04 seconds. It can be seen that under the premise of real-time adjustment of connection planning time, the optimization model can satisfy the passenger’s dynamic demand to a greater extent, and effectively reduce the planning path error, shorten the distance and travel time of passengers, and the result is better than that of the flexible bus scheduling model which ignores the change of connection travel time.


2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Dianhui Chu ◽  
Chunshan Li ◽  
Xiaofei Xu ◽  
Xiaofeng Zhang

How to find the optimal transportation route in sea-trade is very important for the logistics industry. The traditional routing problem is solved by performing the combinatorial optimization over a specified transportation network. Facing the huge network extracted from the foreign trading industry as well as the complex constraints, it is impossible for the traditional optimization methods to find the solution in a short time, which motivates our work. In this paper, we first carefully study the property of foreign trade network, and then convert the transportation network into a hierarchical one and propose a novel framework based on graphical model to solve this large scale network optimization problem. The experimental results demonstrate that our approach is superior to the famous ant colony optimization algorithm (ACO) in terms of accuracy and the time spent.


2013 ◽  
Vol 864-867 ◽  
pp. 2804-2807 ◽  
Author(s):  
Hai Long Sun ◽  
Li Yan Yue ◽  
Sheng Yong Yao

In the process of urban disaster emergency rescue, vehicle route optimization has become a key problem of city emergency rescue. In order to improve the emergency rescue responsiveness, a dynamic vehicle routing optimization model is established, which takes dynamic transportation network as the research object and travel time as the goal. At the same time, an improved ant algorithm is used to solve the model, which achieves the desired objectives.


2019 ◽  
Vol 139 (4) ◽  
pp. 401-408
Author(s):  
Shunya Tanabe ◽  
Zeyuan Sun ◽  
Masayuki Nakatani ◽  
Yutaka Uchimura

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