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Sustainable forestry logistics: Using modified a-star algorithm for efficient timber transportation route optimization

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FOREST POLICY AND ECONOMICS 2025年 173卷

作者： Veisi, Omid Moradi, Mohammad Amin Gharaei, Beheshteh Maleki, Farid Jabbari Rahbar, Morteza Univ Siegen Business Informat & New Media Siegen Germany Univ Toronto Sch Informat Toronto ON Canada Univ Coll Rouzbahan Sch Architecture & Engn Mazandaran Iran Islamic Azad Univ Dept Architecture Damavand Branch Damavand Iran MUT Univ Tehran Telecommun Engn Tehran Iran Iran Univ Sci & Technol Sch Architecture & Environm Design Tehran Iran

The use of brown, recyclable wood resources has significant importance in a country like Canada, given their abundant availability. Nevertheless, the conveyance of these timber resources to wood recycling facilities offers many economic and environmental benefits to pertinent entities. One potential drawback is that the forest ecosystem could endure substantial harm and ultimately disappear if every road were utilized as access points for timber-transporting vehicles. The main aim of this project is to collect the maximum amount of recycled wood using a minimum forest road network to achieve smart logistics systems. An additional objective of this research is to ascertain the optimal search radius and blocks of area for conducting woodland searches at each station, taking into consideration the quantity of collected wood. The methodology employed in this study involves the application of geometric networking integration techniques in Geographic Information Systems to generate integrated maps using the forest route data, and a modified a-star algorithm is utilized to efficiently determine the optimal wood recycling forest road. The study's results suggest that using the Modified a-star algorithm enables a recycling rate between 50 % and 70 % for the collection of all wood items while utilizing just 10 % of the road network. This approach and technique might be used in future research conducted in countries with similar forest coverage levels.

关键词： Sustainable transportation a-star algorithm Forest road network Forestry logistics Route optimization

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a-star algorithm Based On-Demand Routing Protocol for Hierarchical LEO/MEO Satellite Networks 3

A-Star Algorithm Based On-Demand Routing Protocol for Hierar...

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IEEE International Conference on Big Data

作者： Ji, Xuezhi Liu, Lixiang Zhao, Pei Wang, Dapeng Chinese Acad Sci Inst Software Sci & Technol Integrated Informat Syst Lab Beijing Peoples R China

ISBN: (纸本)9781479999255

An a-star algorithm based on-demand routing (ASOR) protocol for hierarchical Low Earth Orbit (LEO)/Middle Earth Orbit (MEO) satellite networks is proposed and evaluated in this paper. The protocol uses the improved A-star to decrease the searching area and the computing cost, which is significant for real time data. It also calculates the optimal path on-demand, which can guarantee an optimal path and avoid broken nodes. The simulation results show that ASOR has a better performance on convergence time and end-to-end delay compared to the centralized routing protocol SGRP.

关键词： satellite networks routing protocol a-star algorithm on-demand routing

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a-star algorithm for Energy Efficient Routing in Wireless Sensor Network

A-Star Algorithm for Energy Efficient Routing in Wireless Se...

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4th International Conference on Network Security and Applications (CNSA 2011)

作者： Rana, Keyur Zaveri, Mukesh Sarvajanik Coll Engn & Technol Dept Comp Engn Surat India Sardar Vallabhbhai Natl Inst Technol Surat India

ISBN: (纸本)9783642225420

Various routing protocols have been designed and developed for Wireless Sensor Networks (WSN). They face various challenges. Sensor nodes are strongly energy and storage constrained and failure rate of sensor node is very high. While sending data to the Base station some routine mechanisms which consider all these parameters, are needed to extend life of the network. There are several techniques for routing in WSN for data gathering with aggregation and for data gathering without aggregation. Using Minimum transmission energy model and Minimum hop routing model techniques it may happen that the same path is used for more times and nodes on this route gets drain from energy. This leads to network partition and routing algorithm failure. In this paper, we have presented routing algorithm based on informed search. We have used a-star algorithm to search optimal route from source to the destination in such a way that overall life of network is extended. We have used a pre-defined minimum energy level (Level1) for sensor nodes so that sensor node don't participate in routine if its residual energy level is below this level and other better path is available. If there exist no such path, then this node can be part of routing.

关键词： Wireless sensor network Routine algorithm a-star algorithm Energy aware routine in WSN

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Improved a-star algorithm for Power Line Inspection UAV Path Planning

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ENERGIES 2024年第21期17卷 5364页

作者： Li, Yanchu Dong, Xinzhou Ding, Qingqing Xiong, Yinlong Liao, Huilian Wang, Tao Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Guangdong Power Grid Co Ltd Foshan Power Supply Bur Foshan 528000 Peoples R China State Grid Henan Elect Power Co DC Ctr Zhengzhou 450018 Peoples R China

The operational areas for unmanned aerial vehicles (UAVs) used in power line inspection are highly complex;thus, the best path planning under known obstacles is of significant research value for UAVs. This paper establishes a three-dimensional spatial environment based on the gridding and filling of two-dimensional maps, simulates a variety of obstacles, and proposes a new optimization algorithm based on the a-star algorithm, considering the unique dynamics and control characteristics of quadcopter UAVs. By utilizing a novel heuristic evaluation function and uniformly applied quadratic B-spline curve smoothing, the planned path is optimized to better suit UAV inspection scenarios. Compared to the traditional a-star algorithm, this method offers improved real-time performance and global optimal solution-solving capabilities and is capable of planning safer and more realistic flight paths based on the operational characteristics of quadcopter UAVs in mountainous environments for power line inspection.

关键词： UAV power line inspection path planning a-star algorithm

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Improved a-star algorithm based on multivariate fusion heuristic function for autonomous driving path planning

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2023年第7期237卷 1527-1542页

作者： Wang, Pengyu Liu, Yanglin Yao, Weimin Yu, Yuanbin Jilin Univ State Key Lab Automot Simulat & Control 5988 Renmin St Changchun 130022 Jilin Peoples R China

Path planning is a fundamental problem in the aspect of autonomous driving. A-star (A*) algorithm is a heuristic algorithm for path planning. However, there are two problems need to be solved in the traditional a-star algorithm: firstly, the tracking error caused by vehicle speed and vehicle size are not considered in path planning;secondly, the kinematics constraints of the vehicle itself and the smoothness of the path in the actual driving process are not considered. Therefore, this paper proposes an improved a-star algorithm to address the above deficiencies. By designing the collision cost heuristic function based on the position of obstacles, the vehicle contour and speed are considered and the vehicle safety is improved by setting a safe space around the vehicle, and establishing a steering cost heuristic function based on the control of heading angle difference, the vehicle dynamics constraints are satisfied, so as to improve the feasibility of path planning. The experimental results show that the improved a-star algorithm can avoid vehicle contours collision at different speeds and output a smoother path, and effectively generate higher quality path.

关键词： Autonomous driving path planning a-star algorithm heuristic function

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Geometric a-star algorithm: An Improved a-star algorithm for AGV Path Planning in a Port Environment

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IEEE ACCESS 2021年 9卷 59196-59210页

作者： Tang, Gang Tang, Congqiang Claramunt, Christophe Hu, Xiong Zhou, Peipei Shanghai Maritime Univ Sch Logist Engn Shanghai 201306 Peoples R China Naval Acad Res Inst F-29240 Brest France Guangdong Polytech Normal Univ Sch Mech Engn Guangzhou 510665 Peoples R China

This research introduces a path planning method based on the geometric a-star algorithm. The whole approach is applied to an Automated Guided Vehicle (AGV) in order to avoid the problems of many nodes, long-distance and large turning angle, and these problems usually exist in the sawtooth and cross paths produced by the traditional a-star algorithm. First, a grid method models a port environment. Second, the nodes in the close-list are filtered by the functions P(x, y) and W(x, y) and the nodes that do not meet the requirements are removed to avoid the generation of irregular paths. Simultaneously, to enhance the stability of the AGV regarding turning paths, the polyline at the turning path is replaced by a cubic B-spline curve. The path planning experimental results applied to different scenarios and different specifications showed that compared with other seven different algorithms, the geometric a-star algorithm reduces the number of nodes by 10% similar to 40%, while the number of turns is reduced by 25%, the turning angle is reduced by 33.3%, and the total distance is reduced by 25.5%. Overall, the simulation results of the path planning confirmed the effectiveness of the geometric a-star algorithm.

关键词： a-star algorithm automated guided vehicle (AGV) grid method path planning

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Efficient and optimal penetration path planning for stealth unmanned aerial vehicle using minimal radar cross-section tactics and modified a-star algorithm

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ISA TRANSACTIONS 2023年 134卷 42-57页

作者： Zhang, Zhe Jiang, Ju Wu, Jian Zhu, Xiaozhou Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 211106 Peoples R China Nanchang Hangkong Univ Coll Informat Engn Nanchang 330063 Peoples R China Acad Mil Sci Peoples Liberat Army Natl Innovat Inst Def Technol Beijing 100071 Peoples R China

Penetration path planning for stealth unmanned aerial vehicles (SUAVs) in the integrated air defense system (IADS) has been a hot research topic in recent years. The present study examines penetration path planning in different threat environments. Firstly, for the complex terrain and static radar threats, a modified a-star algorithm containing the bidirectional sector expansion and variable step search strategy is proposed to elude static threats rapidly. Then, with regard to bandit threats, the minimal radar cross-section (RCS) tactics are presented to achieve path replanning. Furthermore, the combinatorial methodology of the minimum RCS tactics and the modified a-star algorithm is applied to achieve the dynamic path planning for SUAV. The simulation results indicate that the modified a-star algorithm and minimal RCS tactics can significantly reduce the probability of radar system, which has better superiority in calculation efficiency, path cost and safety. And the minimal RCS tactics have better real-time performance and are more convenient in dealing with dynamic threats, which enhances the survivability of SUAV and verifies the effectiveness of the proposed methodology.(c) 2022 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Stealth unmanned aerial vehicles (SUAVs) Path planning Minimal radar cross-section (RCS) tactics Moving target a-star algorithm

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ASL-DWA: An Improved a-star algorithm for Indoor Cleaning Robots

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IEEE ACCESS 2022年 10卷 99498-99515页

作者： Liu, Haoxin Zhang, Yonghui Hainan Univ Sch Informat & Commun Engn Haikou 570288 Hainan Peoples R China

The traditional a-star algorithm has many search nodes, and the obtained path has polylines and cannot avoid local unknown obstacles. In response to these problems, this paper proposes a new improved a-star algorithm suitable for indoor cleaning robots, called ASL-DWA (A star Leading Dynamic Window Approach). First, to solve the problem of many search nodes in the a-star algorithm, a new hybrid heuristic function that combines Euclidean distance and point-to-line distance is proposed, thereby reducing the number of search nodes. Then, to solve the problem that the a-star algorithm has a polyline path and cannot avoid local unknown obstacles, this paper designs the global path yaw angle according to the relationship between the real-time position of the robot and the global path, which is added as a score item to the traditional score function. A decay coefficient with prediction function is also added to the score function to reduce the risk of the algorithm falling into local optima. Finally, a mechanism to adaptively adjust the coefficient according to the distance between the robot and the target point is designed, thereby realizing ASL-DWA. The ASL-DWA algorithm is tested in three indoor environments and compared with traditional algorithms. The experimental results show that ASL-DWA can meet the path planning requirements of mobile robots in indoor environments, and has obvious advantages over traditional algorithms.

关键词： Robots Heuristic algorithms Path planning Cleaning Prediction algorithms Mobile robots Indoor environment Indoor cleaning robot a-star algorithm hybrid heuristic function global path yaw angle adaptive weighted score function

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Accelerating reconfiguration for VLSI arrays with a-star algorithm

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IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING 2018年第10期13卷 1511-1519页

作者： Qian, Junyan Zhou, Zhide Zhao, Lingzhong Zhang, Jingwei Li, Fengying Guilin Univ Elect Technol Guangxi Key Lab Trusted Software Guilin 541004 Peoples R China

We describe a novel technique to speed up the reconfiguration for the very large scale integration (VLSI) arrays. We propose an efficient algorithm, making use of the idea of the a-star algorithm, for accelerating the reconfiguration of the VLSI processor arrays to meet the real-time constraints of embedded systems. The proposed algorithm treats the problem of constructing a local optimal logical column that has the minimum number of long interconnects as a shortest path problem. Then the local optimal column can be constructed by utilizing the a-star algorithm with the appropriate heuristic strategy. We prove that the proposed method can find the shortest local logical column. Simulation experiments reveal that the proposed algorithm can greatly reduce the number of visits to the fault-free processing elements (PEs) for constructing a local optimal logical column and effectively decrease the reconfiguration running time. Experimental results show that the computation time can be reduced by more than 38.64% for a 128x128 host array with fault density of 20%, without loss of harvest. (c) 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

关键词： reconfiguration VLSI array shortest path a-star algorithm

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Modified a-star algorithm for modular plant land transportation

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2018年第12期32卷 5563-5571页

作者： Kang, Nam Kyu Son, Ho Joon Lee, Soo-Hong Yonsei Univ Dept Mech Engn Seoul 03722 South Korea

Many common path optimization algorithms are available. However, problems arise when a general route optimization algorithm is applied to land transportation of large cargo, such as a modular plant. The large and heavy structure of a modular plant can lead to a loss of time depending on the curve of the road. This problem is more critical when traveling through large turns, which may also cause mechanical problems. Therefore, curves are essential parameters for modular plant land transportation. In this research, we show the importance of angles in the path via multi-body dynamic simulations and finite element analysis. Based on these results, we constructed a pathfinding algorithm that considers the importance of angles. The traditional a-star algorithm considers only distance as a cost, whereas our modified a-star algorithm considers both distance and angle as costs. Our goal is to improve traditional a-star algorithms and optimize them for modular plant land transportation.

关键词： a-star algorithm Multi-body dynamics simulation Plant land transportation Optimized path finding

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