Multi-constrained Optimal Path Search Algorithms

2014 ◽  
pp. 355-366
Author(s):  
Jinling Bao ◽  
Bin Wang ◽  
Shuchao Yan ◽  
Xiaochun Yang
Keyword(s):  
Optimal Path ◽  
Search Algorithms ◽  
Path Search

scholarly journals Comparative Analysis of Optimal Path Search Algorithms

2020 ◽  
Vol 6 (12) ◽  
pp. 248-255
Author(s):  
A. Sultanova
Keyword(s):  
Comparative Analysis ◽  
Shortest Path ◽  
Mobile Robotics ◽  
Optimal Path ◽  
Search Algorithms ◽  
Traffic Planning ◽  
Level System ◽  
Dijkstra Algorithm ◽  
Path Search ◽  
Grid Algorithms

This article discusses widely used algorithms for finding optimal paths. Currently, there is a fairly wide list of algorithms for the problem of finding the shortest path, and is actively used in mobile robotics to find the optimal route. The article offers a two-level system that performs traffic planning. Comparative analysis of various search methods was carried out: their length, complexity, and a number of turning points. The purpose of the article is to study and compare algorithms from the field of artificial intelligence for finding the shortest path in a maze and a hexagonal grid. Algorithms under study: A* (star), Dijkstra algorithm, BFS, DFS, and Greedy algorithm. Algorithms are compared based on two criteria: the length of the found path and the time it takes to find the path. The results, presented analytically and graphically, show the application of five algorithms for mazes with different size and number of obstacles.

scholarly journals Identification of Optimal Path in Power System Network Using Bellman Ford Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
S. Hemalatha ◽  
P. Valsalal
Keyword(s):  
Power System ◽  
Transmission Line ◽  
Shortest Path ◽  
Voltage Stability ◽  
Optimal Path ◽  
Power Balance ◽  
Line Voltage ◽  
System Components ◽  
Path Search ◽  
Search Guidance

Power system network can undergo outages during which there may be a partial or total blackout in the system. In that condition, transmission of power through the optimal path is an important problem in the process of reconfiguration of power system components. For a given set of generation, load pair, there could be many possible paths to transmit the power. The optimal path needs to consider the shortest path (minimum losses), capacity of the transmission line, voltage stability, priority of loads, and power balance between the generation and demand. In this paper, the Bellman Ford Algorithm (BFA) is applied to find out the optimal path and also the several alternative paths by considering all the constraints. In order to demonstrate the capability of BFA, it has been applied to a practical 230 kV network. This restorative path search guidance tool is quite efficient in finding the optimal and also the alternate paths for transmitting the power from a generating station to demand.

scholarly journals A Method for Obtaining Optimal Path in Angle and Avoiding Collision for Robotic Belt Grinding

2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
Tie Zhang ◽  
Xiaohong Liang ◽  
Ye Yu ◽  
Bin Zhang
Keyword(s):  
Coordinate System ◽  
Search Algorithm ◽  
Optimal Path ◽  
Recursive Method ◽  
Coordinate Plane ◽  
Angular Variation ◽  
Belt Grinding ◽  
Robotic Grinding ◽  
Path Search ◽  
Robotic Belt Grinding

The angular variation of the joints may be large, and collision between workpieces and tools may occur in robotic grinding. Therefore, this paper proposes an optimal robotic grinding path search algorithm based on the recursive method. The algorithm is optimized by changing the position of the tool coordinate system on the belt wheel; thus, the pose of the robot during grinding is adjusted. First, the position adjustment formula of the tool coordinate system is proposed, and a coordinate plane is established to describe the grinding path of the robot based on the position adjustment formula. Second, the ordinate value of this coordinate plane is dispersed to obtain the search field of the optimal robotic grinding path search algorithm. Third, an optimal robotic grinding path search algorithm is proposed based on the recursive method and single-step search process. Finally, the algorithm is implemented on the V-REP platform. Robotic grinding paths for V-shaped workpieces and S-shaped workpieces are generated using this algorithm, and a grinding experiment is performed. The experimental results show that the robotic grinding paths generated by this algorithm can smoothly complete grinding operations and feature a smaller angular variation of the joint than other methods and no collision.

The Optimal Path Search Algorithm for Spread of Flame and Smoke in Fire Simulation

2013 ◽  
Author(s):  
Eunju Kim ◽  
◽  
YONGZHE XU ◽  
Kyunjoo Lee ◽  
Jaesug Ki ◽  
...  
Keyword(s):  
Search Algorithm ◽  
Optimal Path ◽  
Fire Simulation ◽  
Path Search ◽  
In Fire

scholarly journals Research on Large-Scale Road Network Partition and Route Search Method Combined with Traveler Preferences

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
De-Xin Yu ◽  
Zhao-Sheng Yang ◽  
Yao Yu ◽  
Xiu-Rong Jiang
Keyword(s):  
Data Storage ◽  
Road Network ◽  
Large Scale ◽  
Search Algorithm ◽  
Optimal Path ◽  
Search Method ◽  
Urban Road Network ◽  
Urban Road ◽  
Path Search ◽  
Route Search

Combined with improved Pallottino parallel algorithm, this paper proposes a large-scale route search method, which considers travelers’ route choice preferences. And urban road network is decomposed into multilayers effectively. Utilizing generalized travel time as road impedance function, the method builds a new multilayer and multitasking road network data storage structure with object-oriented class definition. Then, the proposed path search algorithm is verified by using the real road network of Guangzhou city as an example. By the sensitive experiments, we make a comparative analysis of the proposed path search method with the current advanced optimal path algorithms. The results demonstrate that the proposed method can increase the road network search efficiency by more than 16% under different search proportion requests, node numbers, and computing process numbers, respectively. Therefore, this method is a great breakthrough in the guidance field of urban road network.

Optimal path search and control of mobile robot using hybridized sine-cosine algorithm and ant colony optimization technique

2020 ◽  
Vol 47 (4) ◽  
pp. 535-545
Author(s):  
Saroj Kumar ◽  
Dayal R. Parhi ◽  
Manoj Kumar Muni ◽  
Krishna Kant Pandey
Keyword(s):  
Mobile Robots ◽  
Ant Colony Optimization ◽  
Optimization Technique ◽  
Optimal Path ◽  
Ant Colony ◽  
Target Point ◽  
Multiple Mobile Robots ◽  
Content Type ◽  
Path Search ◽  
Sine Cosine Algorithm

Purpose This paper aims to incorporate a hybridized advanced sine-cosine algorithm (ASCA) and advanced ant colony optimization (AACO) technique for optimal path search with control over multiple mobile robots in static and dynamic unknown environments. Design/methodology/approach The controller for ASCA and AACO is designed and implemented through MATLAB simulation coupled with real-time experiments in various environments. Whenever the sensors detect obstacles, ASCA is applied to find their global best positions within the sensing range, following which AACO is activated to choose the next stand-point. This is how the robot travels to the specified target point. Findings Navigational analysis is carried out by implementing the technique developed here using single and multiple mobile robots. Its efficiency is authenticated through the comparison between simulation and experimental results. Further, the proposed technique is found to be more efficient when compared with existing methodologies. Significant improvements of about 10.21 per cent in path length are achieved along with better control over these. Originality/value Systematic presentation of the proposed technique attracts a wide readership among researchers where AI technique is the application criteria.

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