An Improved Heuristic Function for A∗-Based Path Search in Detailed Routing

Unmanned aerial vehicles (UAVs) are used in team for detecting targets and keeping them in its sensor range. There are various algorithms available for searching and monitoring targets. The complexity of the search algorithm increases if the number of nodes is increased. This paper focuses on multi UAVs path planning and Path Finding algorithms. Number of Path Finding and Search algorithms was applied to various environments, and their performance compared. The number of searches and also the computation time increases as the number of nodes increases. The various algorithms studied are Dijkstra's algorithm, Bellman Ford's algorithm, Floyd-Warshall's algorithm and the AStar algorithm. These search algorithms were compared. The results show that the AStar algorithm performed better than the other search algorithms. These path finding algorithms were compared so that a path for communication can be established and monitored.

This paper proposes a parallel shortest path-searching algorithm and implements it on a newly structured parallel reconfigurable processor, DAPDNA-2 (IPFlex Inc). Routing determines the shortest paths from the source to the ultimate destination through intermediate nodes. In open shortest path first (OSPF), Dijkstra's shortest path algorithm, which is the conventional one, finds the shortest paths from the source on a program counter-based processor. The calculation time for Dijkstra's algorithm is O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) when the number of nodes is N. When the network scale is large, calculation time required by Dijkstra's algorithm increases rapidly. It's very difficult to compute Dijkstra's algorithm in parallel because of the need for previous calculation results, so Dijkstra's algorithm is unsuitable for parallel processors. Our proposed scheme finds the shortest paths using a simultaneous multi-path search method. In contrast with Dijkstra's algorithm, several nodes can be determined at one time. Moreover, we partition the network into different groups (network groups) and find the all-node pair's shortest path in each group using a pipeline operation. Networks can be abstracted, and the shortest paths in very large networks can be found easily. The proposed scheme can decrease calculation time from O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) to O(N) using a pipeline operation on DAPDNA-2. Our simulations show that the proposed algorithm uses 99.6% less calculation time than Dijkstra's algorithm. The proposed algorithm can be applied to the very large Internet network designs of the future.

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and various such systems have been recently studied. For a successful economic ship routing system, an efficient algorithm is needed to search an optimal geographical path, and most of the previous systems were approaching to that problem through a minimal static-cost path search algorithm based on the Dijkstra algorithm. To apply that kind of search algorithm, the cost of every edge assigned with the estimated fuel consumption should be constant. However, that assumption is not practical at all considering that the actual fuel consumption is determined by the weather condition when the ship will pass the edge. To overcome such a limitation, we propose a new optimal ship routing system based on a minimal dynamic-cost path search algorithm by properly modifying the Dijkstra algorithm. In addition, we propose a method which efficiently reduces the search space by using the algorithm to decrease the running time. We compared our system with the shortest path-based sailing method over ten testing routes and observed that the former reduced the estimated fuel consumption than the latter by 2.36% on average and the maximum 4.82% with little difference of estimated time of arrival.

In the event of a disaster, most of the current evacuation path search algorithms are based on minimizing the travel cost to each shelters. Since the shelters usually have limited capacities, the vehicle evacuation time may be lengthened to search the alternate shelter if the first chosen shelter is full. A new algorithm is presented in this study which will minimize the vehicle evacuation time by searching a shelter with consideration of its capacity. Link based Dijkstra which is most widely used path search algorithm is utilized and the traffic shall be assigned according to the dynamic transportation network load model. The dynamic network loading model is used to express how a group of vehicles is moving an actual network through the moving cell model that best describes the traffic flow characteristics of the group of vehicles. The suggested algorithm is applied to the example traffic to compare the results where the shelter capacity has been considered in determining the path information and the results where it has not been considered. This study observed and concluded that the total vehicle evacuation time is practically reduced where the shelter capacity has been considered in determining the evacuation path.

Geographic information systems related to the position of objects in the earth's surface such as the position of the attractions that are connected with roads. Streets that are interconnected to form a complex network. Usually people use our manual to find the shortest route of an object toward a particular object but it is less than optimal because it requires precision and a long time. The shortest route search problem has been solved by several algorithms such as Dijkstra's algorithm, Astar, Floyd Warshall, Ant Colony and others. Based on this final task is to discuss the implementation of the shortest route to the geographic information system of tourism in a city using the distance parameter. City to be addressed is Sawahlunto has 12 attractions that are connected with road network. Shortest path search algorithm used is Dijkstra's and Astar algorithm. Geographic information system of tourism is displayed in a web form, with the programming language PHP, database PosgreSQL and support PostGIS and pgRouting. Based on the testing of these applications can provide the shortest route along the travel distance to and from 12 tourist sites in Sawahlunto. Astar algorithm is faster in the process of finding the shortest route instead of Dijkstra's algorithm with an average gap of 40 ms. Application also provides information supporting the tourism profile information, attractions, culture, and contacts. Keyword : shortest path, Dijkstra algorithm, Astar algorithm, geographic information system

The power line communication detection device is the core equipment of the low-carbon building energy Internet. Although the power line carrier communication (HPLC) adopted by it has a fast transmission speed, its path search signaling communication reliability is low, which seriously restricts the communication performance of the relay. The two-way automatic communication system (TWACS) has high reliability, but its path search speed is slow, which seriously affects the timeliness of communication. In order to improve the coverage and reliability of power line communication detection device in energy Internet information perception, an improved multi-mode fusion communication path search algorithm based on HPLC and TWACS is proposed. The algorithm uses TWACS as the path search signaling of PLC downlink communication, uses PLC to transmit main data information, and uses TWACS to transmit broadcast information and path relay instructions

Generative models for grid-based and image-based pathfinding

Shortest pathfinding is an algorithm that can be used for the nearest path search solution, in this study the use of the shortest pathfinding method in the best path search for firefighting teams travels to the location of the fire incident. Case studies were conducted in a city in the United States called Naperville, the data taken in the form of locations from the fire department, several important points in the city and the latest data location of the fire incident. The shortest pathfinding algorithm used is hybrid fuzzy Dijkstra, the algorithm is a development of the Dijkstra algorithm, where the algorithm can use more than one consideration parameter for determining the best path, the dataset and various parameters are grouped based on fuzzy algorithms and then processed using Dijkstra algorithm. The use of fuzzy algorithms that group data based on data ranges can speed up the search process at each level of the graph matrix because some data that is almost the same will be grouped into one data range. Based on the research conducted, it can be seen that the method was successful in determining the best path to the location of the fire incident, based on several other route choices.

Microrobot has been developed for the manipulation of micro- and nanoscale objects for many biological and manufacturing tasks. However, there are still challenges in the collision-free operation of microrobots in multiple scenarios. Essential functions, such as path planning and autonomous and adaptive navigation in dynamic environments, are urgently needed to implement microrobots in practical scenarios. Here, we implement path planning and the autonomous navigation of microrobots in 2D static obstacle scenarios and micro-mazes. A probabilistic-based RRT algorithm is employed to speed up the path search in static obstacle scenarios. The Dijkstra algorithm is employed in the micro-maze navigation of the microrobot to avoid the narrow and long pipeline effect. To further ease the active manipulation of magnetic mobile microrobots, a handle-based interactive operation is developed to realize the operational tasks in the three-dimensional space based on artificial vision planning and navigation, which improves the interactivity and flexibility of the system, and supplements the current limitation of autonomous navigation on the three-dimensional space.

Fire is one of the disasters that often occur in everyday life. There has been much research done to build a fire Simulator. In this paper, we propose a fire Simulator that is applied optimal path search algorithm to arrange the quick evacuation. This simulator considers the structure of a building and the location where the fire has initially occurred, applying it to the simulator. Especially when implementing the training simulation for firefighters, optimized evacuation path for the required virtual rescuer awaiting rescue was informed to implement more realistic firefighting training simulator. For the simulation for the test, fixed data was set to apply the shortest path search algorithm and flame smoke spread algorithm. As a result of the test, the optimized path was derived through avoiding the flame occurred from flame smoke spread algorithm and following the shortest path search algorithm.

Path planning is one of the important directions in the field of intelligent vehicles research. Traditional path planning algorithms generally use Dijkstra algorithm, Breadth-First-Search (BFS) algorithm and A* algorithm. Dijkstra algorithm is a search-based algorithm, which can search to an optimal path, but the disadvantage is too many expansion nodes, which leads to insufficient search efficiency. BFS algorithm is a heuristic search algorithm, which reduces the disadvantage of too many expansion nodes and improves the search efficiency by heuristic function. A* algorithm is a heuristic search algorithm that combines Dijkstra’s algorithm and BFS algorithm, which has higher search efficiency and can search to an optimal path at the same time, but it is still lacking in the search mode and smoothness of the planned route. This paper first introduces the general path planning algorithm, then introduces and analyzes the A* algorithm, and proposes improvement measures for its shortcomings; finally, the executability and effectiveness of the improved algorithm are tested using simulation, and compared with the traditional A* algorithm, and the results show that the improved A* algorithm has good effect on path planning of intelligent vehicles.

The use of the mass spectral simulation system, MASSIS, is reported and its performance has been evaluated. The search for substructures matching with fragments stored in four pivot databases was realised using the Ullmann algorithm. Special cleavage rules, such as the McLafferty rearrangement, the retro-Diels-Alder reaction, elimination of a neutral small molecule and oxygen migration, are processed through shortest path and depth-first search algorithms. For a search in the database of small fragments, the key step is to determine the tautomeric fragments; then a match can be obtained using a subgraph isomorphism algorithm. A string match is used to determine peak intensity. If the limited environment of an atom is the same as that found in the database of relationships between fragment and intensity, this intensity value is assigned to the query atom. Performance in a set of tests is very important in evaluating the system performance. A comparison of peaks with an intensity greater than 5% (relative) shows that our system has a very high performance figure (> 90% ) for routine organic compounds.

As Industry 5.0 progresses, the demand for zero-touch configuration in industrial automation and smart manufacturing is increasing. This paper proposes a dynamic configuration management framework for Time-Sensitive Networking (TSN), aiming to address the challenges of flexibility and adaptability in dynamic network environments. A zero-touch configuration model is presented for TSN by incorporating a Delay-Aware Shortest Path Search (DASPS) algorithm to improve scheduling success rates. Simulation results demonstrate the ability of the framework to reconfigure networks within 2.67 milliseconds. The DASPS algorithm achieves a scheduling success rate of 70.22% for 1000 TSN flows, in contrast to only 22.23% achieved by the Shortest Path Search (SPS) algorithm. The proposed model effectively adapts to dynamic network changes, guaranteeing real-time data transmission. To further evaluate system adaptability, path entropy is introduced as a metric to quantitatively assess the balance of scheduling outcomes under topological changes. In the event of link failures, path entropy experiences a sharp decline but rapidly recovers after reconfiguration, demonstrating the system’s strong self-healing capability.

Routability is a critical issue in VLSI design flow. To address this issue, the routability-driven placement contests [1, 2] held at ISPD11 and DAC12 promote the development of routability-driven placers such as those in [4-6]. ISPD11 and DAC12 contests adopt metrics that are based on global routing solutions to evaluate the routability of placement solutions. However, such global-routing-based metrics typically ignore local congestion, and they cannot evaluate the actual routability effectively. In this work, we develop a translator that allows us to feed the placement solutions of mPL [3], NTUplace [4], Ripple [5], and SimPLR [6] into a commercial router for detailed routing. We then analyze the detailed routing result of each placement solution to better understand the issues that may cause routing violations. Moreover, we examine the suitability of using the ISPD11 and DAC12 metrics in predicting routability. Our findings indicated that the metrics might not reliably predict actual routability, in terms of the number of (detailed) routing violations.

Routing is a crucial stage in a modern design automation tool flow for advanced technology nodes. Works in the recent open literature tend to divide routing into separate global routing (GR) and detailed routing (DR) steps without addressing the correlation issues (e.g., local nets) between these two steps. In this work, we present TritonRoute-WXL (TR-WXL), a unified global-detailed router capable of delivering design rule check-clean routing solutions in commercial sub-16-nm technologies. The major contributions of TR-WXL include an end-to-end routing framework that closely connects GR and DR, and an improved DR flow. With a code release under a permissive open-source license, TR-WXL achieves unparalleled solution quality in terms of DR and global-detailed routing (GDR) as compared to known best solutions from all published academic routers.