Method for Determining the Location of Highway Passenger Transportation Hubs Using POI Data and the Dijkstra Algorithm in Large City

Li, Hui; Tong, Pei; Zhang, Xu

doi:10.1155/2022/2189598

Cited by 6 publications

(4 citation statements)

References 25 publications

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“…In the similar problem of shortest path, the Dijkstra algorithm, Floyd algorithm, A* algorithm and other algorithms are commonly used to solve the problem. However, the time complexity of the single iteration path search process of Floyd algorithm is higher than that of Dijkstra algorithm, and the algorithm speed is slower ( Li, Tong & Zhang, 2022 ). The Bellman-Ford algorithm has the problems of extreme redundancy and low efficiency ( Wang, 2018 ).…”

Section: Solving Methodsmentioning

confidence: 99%

A hybrid GA-PSO strategy for computing task offloading towards MES scenarios

Sun

Wang³

et al. 2023

PeerJ Computer Science

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As a new type of computing paradigm closer to service terminals, mobile edge computing (MEC), can meet the requirements of computing-intensive and delay-sensitive applications. In addition, it can also reduce the burden on mobile terminals by offloading computing. Due to cost issues, results in the deployment density of mobile edge servers (MES) is restricted in real scenario, whereas the suitable MES should be chosen for better performance. Therefore, this article proposes a task offloading strategy under the sparse MES density deployment scenario. Commonly, mobile terminals may reach MES through varied access points (AP) based on multi-hop transmitting mode. The transmission delay and processing delay caused by the selection of AP and MES will affect the performance of MEC. For the purpose of reducing the transmission delay due to system load balancing and superfluous multi-hop, we formulated the multi-objective optimization problem. The optimization goals are the workload balancing of edge servers and the completion delay of all task offloading. We express the formulated system as an undirected and unweighted graph, and we propose a hybrid genetic particle swarm algorithm based on two-dimensional genes (GA-PSO). Simulation results show that the hybrid GA-PSO algorithm does not outperform state-of-the-art GA and NSA algorithms in obtaining all task offloading delays. However, the workload by standard deviation approach is about 90% lower than that of the GA and NSA algorithms, which effectively optimizes the performance of load balancing and verifies the effectiveness of the proposed algorithm.

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Section: Solving Methodsmentioning

confidence: 99%

A hybrid GA-PSO strategy for computing task offloading towards MES scenarios

Sun

Wang³

et al. 2023

PeerJ Computer Science

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“…The greedy principle in Dijkstra's algorithm always chooses the position with the smallest weight and includes it in the solution set [97] [98]. It performs calculations against all possibilities to find the smallest weight from each node to node [99] [100]. The mechanism of Dijkstra's algorithm can be explained in the following steps:…”

Section: 𝐾 𝑤ℎ𝑒𝑒𝑙 = 2𝜋𝑟mentioning

confidence: 99%

Application of Odometry and Dijkstra Algorithm as Navigation and Shortest Path Determination System of Warehouse Mobile Robot

Ubaidillah,

Sukri

2023

Journal of Robotics and Control

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One of the technologies in the industrial world that utilizes robots is the delivery of goods in warehouses, especially in the goods distribution process. This is very useful, especially in terms of resource efficiency and reducing human error. The existing system in this process usually uses the line follower concept on the robot's path with a camera sensor to determine the destination location. If the line and destination are not detected by the sensor or camera, the robot's navigation system will experience an error. it can happen if the sensor is dirty or the track is faded. The aim of this research is to develop a robot navigation system for efficient goods delivery in warehouses by integrating odometry and Dijkstra's algorithm for path planning. Holonomic robot is a robot that moves freely without changing direction to produce motion with high mobility. Dijkstra's algorithm is added to the holonomic robot to obtain the fastest trajectory. by calculating the distance of the node that has not been passed from the initial position, if in the calculation the algorithm finds a shorter distance it will be stored as a new route replacing the previously recorded route. the distance traversed by the djikstra algorithm is 780 mm while a distance of 1100 mm obtains the other routes. The time for using the Djikstra method is proven to be 5.3 seconds faster than the track without the Djikstra method with the same speed. Uneven track terrain can result in a shift in the robot's position so that it can affect the travel data. The conclusion is that odometry and Dijkstra's algorithm as a planning system and finding the shortest path are very efficient for warehouse robots to deliver goods than ordinary line followers without Dijkstra, both in terms of distance and travel time.

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“…D* algorithm also have widespread use in other fields. In 2022, Li Hui, Tong Pei and Zhang Xu brought forward a new method of determining the location for highway passenger transportation hubs by D* [7]. Their results can help improve transportation convenience and boost regional economy growth.…”

Section: Dijkstra Algorithmmentioning

confidence: 99%

“…Besides, the path-planning algorithms have many advantages compared with manpower, especially in complex and dangerous environment. Therefore, these algorithms are also used in unmanned ships, coal mining and city planning [4][5][6][7]. Third, path-planning algorithms have wide application in agriculture.…”

Section: Introductionmentioning

confidence: 99%

The Research Progress of Path Planning Algorithms

Huang

2023

HSET

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At present, path-planning for mobile robots is a hot problem. In the previous scientific research, A*, Dijkstra, rapidly-exploring random tree (RRT) and many other algorithms have appeared. To provide a clearer understanding of these algorithms, this article organized the idea and development of Q-learning, A* algorithm, ant colony algorithm, RRT algorithm and Dijkstra algorithm. According to the time order, this article researched several applications of the five algorithms respectively. Besides, optimization of the five algorithms in the past few years were listed. There are also examples of combined algorithms, which have better efficiency compared to using one algorithm alone. By analyzing the five algorithm and their optimization, the common problem and solution was found. The common problem of these algorithms is that a shorter and smoother path needs to be solved and the convergence speed needs accelerating. At present, the main solution can be divided into two aspects. One is to improve the algorithm itself, and the other is to combine different algorithms. In the future, more kinds of combined algorithms will emerge, and a better solution of path planning can be obtained to improve efficiency and reduce energy cost.

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Method for Determining the Location of Highway Passenger Transportation Hubs Using POI Data and the Dijkstra Algorithm in Large City

Cited by 6 publications

References 25 publications

A hybrid GA-PSO strategy for computing task offloading towards MES scenarios

A hybrid GA-PSO strategy for computing task offloading towards MES scenarios

Application of Odometry and Dijkstra Algorithm as Navigation and Shortest Path Determination System of Warehouse Mobile Robot

The Research Progress of Path Planning Algorithms

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