Multi-hop routing optimization method based on improved ant algorithm for vehicle to roadside network

2014 ◽  
Vol 11 (3) ◽  
pp. 490-496 ◽  
Author(s):  
Hao Dong ◽  
Xiaohui Zhao ◽  
Liangdong Qu ◽  
Xuefen Chi ◽  
Xinyu Cui
2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jianming Yao ◽  
Mengjie Gu

For an online-shopping company, whether it can provide its customers with customized service is the key to enhance its customers’ experience value and its own competence. A good customized service requires effective integration and reasonable allocation of the company’s supply chain resources running in the background. Based on the analysis of the allocation of supply chain resources in the customized online shopping service mode and its operational characteristics, this paper puts forward an optimization model for the resource allocation and builds an improved ant algorithm to solve it. Finally, the effectiveness and feasibility of the optimization method and algorithm are demonstrated by a numerical simulation. This paper finds that the special online shopping environments lead to many dynamic and uncertain characters of the service demands. Different customized service patterns and their combination patterns should match with different supply chain resource allocations. The optimization model not only reflects the required service cost and delivery time in the objective function, but also considers the service scale effect optimization and the relations of integration benefits and risks. The improved ant algorithm has obvious advantages in flexibly balancing the multiobjective optimizations, adjusting the convergence speed, and adjusting the operation parameters.


2012 ◽  
Vol 468-471 ◽  
pp. 2047-2051 ◽  
Author(s):  
Ai Ling Chen

Vehicle routing optimization problem is one of the major research topics in logistics distribution field. Suitable vehicle routing selection is vital to reduce the logistics cost. The paper presents a hybrid optimization method to solve the vehicle routing problem with time windows. In the hybrid optimization method, discrete particle swarm optimization algorithm is used to assign the customers on routes and simulated annealing (SA) algorithm to avoid becoming trapped in local optimum. The simulation results have shown that the proposed method is feasible and effective for the vehicle routing problem with time windows.


2013 ◽  
Vol 756-759 ◽  
pp. 3941-3945 ◽  
Author(s):  
Wei Yang ◽  
Qian Zhang ◽  
Guo Dong Li

The definition of the cold chain logistics and the problem of the agricultural cold chain logistics are introduced. According to the characteristics of cold chain logistics, exploring the cold chain logistics distribution path optimization method. Based on the model of the agricultural products cold chain logistics distribution routing optimization, particle swarm optimization algorithm is constructed to solve the optimization problem. Taking an example, the results have been conducted finally to demonstrate the effectiveness of the algorithm for agricultural products cold chain logistics distribution routing optimization problem.


Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2590
Author(s):  
Markus Weinhardt ◽  
Mohamed Messelka ◽  
Philipp Käsgen

This article presents CHiPReP, a C compiler for the HiPReP processor, which is a high-performance Coarse-Grained Reconfigurable Array employing Floating-Point Units. CHiPReP is an extension of the LLVM and CCF compiler frameworks. Its main contributions are (i) a Splitting Algorithm for Data Dependence Graphs, which distributes the computations of a C loop to Address-Generator Units and Processing Elements; (ii) a novel instruction clustering and scheduling heuristic; and (iii) an integrated placement, pipeline balancing and routing optimization method based on Simulated Annealing. The compiler was verified and analyzed using a cycle-accurate HiPReP simulation model.


2020 ◽  
Vol 120 (9) ◽  
pp. 1733-1757 ◽  
Author(s):  
Ming K. Lim ◽  
Jianxin Wang ◽  
Chao Wang ◽  
Ming-Lang Tseng

PurposeIncreasing academic communities and practitioners begin to explore a novel method to reduce environmental pollution and realize green logistics delivery. Additionally, China's Statistical Yearbook shows that the number of private cars has reached 165 million in China. Under this background, this study proposes a green delivery method by the combination of sharing vehicle (private cars) and IoT (Internet of things) from the perspective of vehicle energy efficiency and aims to improve the energy efficiency of social vehicles and provides more convenient delivery services.Design/methodology/approachThis study builds an IoT architecture consisting of customer data layer, information collection layer, cloud optimization layer and delivery task execution layer. Especially in the IoT architecture, a clustering analysis method is used to determine the critical value of customers' classification and shared delivery, a routing optimization method is used to solve the initial solution in could layer and shared technology is used in the implementation of shared delivery.FindingsThe results show that the delivery method considering shared vehicles has a positive effect on improving the energy utilization of vehicles. But if all of delivery tasks are performed by the shared vehicle, the application effect may be counterproductive, such as delivery cost increases and energy efficiency decreases. This study provides a good reference for the implementation of green intelligent delivery business, which has a positive effect on the improvement of logistics operation efficiency.Originality/valueThis study designs a novel method to solve the green and shared delivery issues under the IoT environment, which integrates the IoT architecture. The proposed methodology is applied in a real case in China.


2021 ◽  
Author(s):  
Hong Xia ◽  
Jianguo Li ◽  
Yanping Chen ◽  
Ning Lv ◽  
ZhongMin Wang ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document