Shortest Path Finding Algorithm Research Articles

An Improved Path-Finding Method for the Tracking of Centerlines of Tortuous Internal Carotid Arteries in MR Angiography.

Centerline tracking is useful in performing segmental analysis of vessel tortuosity in angiography data. However, a highly tortuous) artery can produce multiple centerlines due to over-segmentation of the artery, resulting in inaccurate path-finding results when using the shortest path-finding algorithm. In this study, the internal carotid arteries (ICAs) from three-dimensional (3D) time-of-flight magnetic resonance angiography (TOF MRA) data were used to demonstrate the effectiveness of a new path-finding method. The method is based on a series of depth-first searches (DFSs) with randomly different orders of neighborhood searches and produces an appropriate path connecting the two endpoints in the ICAs. It was compared with three existing methods which were (a) DFS with a sequential order of neighborhood search, (b) Dijkstra algorithm, and (c) A* algorithm. The path-finding accuracy was evaluated by counting the number of successful paths. The method resulted in an accuracy of 95.8%, outperforming the three existing methods. In conclusion, the proposed method has been shown to be more suitable as a path-finding procedure than the existing methods, particularly in cases where there is more than one centerline resulting from over-segmentation of a highly tortuous artery.

The funnel tree algorithm for finding shortest paths on polyhedral surfaces

In this paper, we present an O-time algorithm for finding the exact shortest paths from a fixed source point to all other vertices on a triangulated polyhedral surface of a polytope in three-dimensional space, where n is the number of faces of the surface. Our algorithm builds a funnel tree by level, to compute such shortest paths. The funnel tree is built by recursively splitting funnels, which are generated as described by An [Optimization, 2018]. Because their left borders are straightest geodesics, funnels are determined explicitly by the law of cosines. Known approaches such as the planar unfolding technique, source images, or projections of ones are avoided in our algorithm. Although these approaches also run in O time in the worst case, our algorithm outperforms the others in practice. Some numerical examples are presented.

(Invited) Towards First-Principles Prediction of Early SEI Formation

Despite decades of work, there is still considerable uncertainty regarding the major components of the solid-electrolyte interface (SEI) and its dynamic formation mechanism as a function of electrolyte and anode composition. Here we present a new data-driven first-principles framework using a combination of high-throughput calculations, reaction networks, machine learning and microkinetic modeling. Our automated methodology is based on a systematic generation of relevant species using a general fragmentation/recombination procedure which provides the basis for a vast thermodynamic reaction landscape, calculated with density functional theory. We explore this landscape using stochastic methods and shortest pathfinding algorithms, which yield the most likely reaction pathways which are then refined with transition state calculations and kinetic information. The results of the framework show promise in being able to automatically recover previous insights on single reaction pathways, as well as successfully predicting the early dynamics and competitive nature of the SEI formation. As examples, we present formation mechanisms of LEMC as compared to LEDC and recover the Peled-like separation of the SEI into inorganic and organic domains resulting from rich reactive competition. By conducting accelerated simulations at elevated temperature, we track SEI evolution, confirming the postulated reduction of lithium ethylene monocarbonate to dilithium ethylene monocarbonate and hydrogen gas. These findings furnish fundamental insights into the dynamics of SEI formation and demonstrate a path forward toward a predictive understanding of electrochemical passivation.

Data-Driven Prediction of Formation Mechanisms of Lithium Ethylene Monocarbonate with an Automated Reaction Network.

Interfacial reactions are notoriously difficult to characterize, and robust prediction of the chemical evolution and associated functionality of the resulting surface film is one of the grand challenges of materials chemistry. The solid-electrolyte interphase (SEI), critical to Li-ion batteries (LIBs), exemplifies such a surface film, and despite decades of work, considerable controversy remains regarding the major components of the SEI as well as their formation mechanisms. Here we use a reaction network to investigate whether lithium ethylene monocarbonate (LEMC) or lithium ethylene dicarbonate (LEDC) is the major organic component of the LIB SEI. Our data-driven, automated methodology is based on a systematic generation of relevant species using a general fragmentation/recombination procedure which provides the basis for a vast thermodynamic reaction landscape, calculated with density functional theory. The shortest pathfinding algorithms are employed to explore the reaction landscape and obtain previously proposed formation mechanisms of LEMC as well as several new reaction pathways and intermediates. For example, we identify two novel LEMC formation mechanisms: one which involves LiH generation and another that involves breaking the (CH2)O-C(═O)OLi bond in LEDC. Most importantly, we find that all identified paths, which are also kinetically favorable under the explored conditions, require water as a reactant. This condition severely limits the amount of LEMC that can form, as compared with LEDC, a conclusion that has direct impact on the SEI formation in Li-ion energy storage systems. Finally, the data-driven framework presented here is generally applicable to any electrochemical system and expected to improve our understanding of surface passivation.

EFFICIENCY COMPARISON OF PATHFINDING ALGORITHMS A* AND DIJKSTRA’S IN TWO DIMENSIONAL GRID

The shortest path finding algorithms are applied more and more in different industries. There are many pathfinding algorithms, but the most of them differ from their modified versions. The goal of this work was to create A* and Dijkstra’s pathfinding algorithms and compare their execution time.

Computing the shortest path with words

Computing with words is a soft computing technique to solve the decision-making problem with the information described in natural language. In this paper, we proposed a generalised Diskrtra's algorithm for finding shortest paths from a source node to every other node in a fuzzy graph where the arc lengths are represented by some natural words taken from natural language. Human being generally describes the arc lengths of any shortest path problem in real life by the terms small, large, some, etc. term which do not supply any natural numbers or fuzzy numbers. We describe those terms as words. Here, we use interval type 2 fuzzy set (IT2FS) to capture the uncertainty of the words. A perceptual computer model is introduced to determine the rank of the shortest path which is a collection of words. A numerical example of transportation network is used to illustrate the effectiveness of the proposed method.

A Regional Protection Partition Strategy Considering Communication Constraints and Its Implementation Techniques

Regional protection based on multisource information of a regional power network depends on communication technology. A partition strategy considering communication constraints and implementation techniques must be considered to realize the regional protection of a large power grid. This paper aims at examining the technical requirements of rapid and reliable regional protection, considering the number of hops as the factor affecting communication between secondary substations and primary substations, and combining this with the equalization of substations. Then, a primary substation selection model of regional protection based on an exhaustive method is proposed using the Floyd–Warshall algorithm (an algorithm for finding shortest paths in a weighted graph). The partition model is further established according to the multifactors that affect the communication delay time for regional protection. Focusing on the N-1 channel fault in the preset region after the formation of the subregions, this paper analyzes the circuitous process of information in an interrupt channel and considers the influence of communication delay time to further improve the partition strategy. Finally, this paper puts forward techniques for partition strategy implementation based on graph theory; an example analysis of an actual power network is also given, and the conclusions of multiple partitions of the same power network are compared and analyzed. Besides this, partition suggestions and theoretical guidance considering actual engineering demands are given.

Computing the Shortest path with Words

Computing with words is a soft computing technique to solve the decision-making problem with the information described in natural language. In this paper, we proposed a generalised Diskrtra's algorithm for finding shortest paths from a source node to every other node in a fuzzy graph where the arc lengths are represented by some natural words taken from natural language. Human being generally describes the arc lengths of any shortest path problem in real life by the terms small, large, some, etc. term which do not supply any natural numbers or fuzzy numbers. We describe those terms as words. Here, we use interval type 2 fuzzy set (IT2FS) to capture the uncertainty of the words. A perceptual computer model is introduced to determine the rank of the shortest path which is a collection of words. A numerical example of transportation network is used to illustrate the effectiveness of the proposed method.

Smart city ambulance for tracking shortest path using global position system

Traffic overcrowding and tidal flow management were identified as major problems in modern urban areas, which have caused much uncomfortable for the ambulance. Moreover, road accidents in the city have been nonstop and to bar the loss of life due to the accidents is even more crucial. To implement this, we introduce a scheme called Smart city ambulance system using shortest path finding algorithm and traffic signals. The main theme behind this scheme is to provide a smooth flow for the ambulance to reach the hospitals in time and thus minifying the expiration. The ambulance driver will send the request to control room. After receiving the request from control room then the ambulance is controlled by the control room which furnishes the most scant route to the ambulance and also controls the traffic light according to the ambulance location and thus reaching the hospital safely. The control room will send the alert message to the hospital. This scheme is fully controlled by control room, thus it controls the traffic lights, helping to reach the hospital in time using the shortest path Dijkstra algorithm

Applying algorithm finding shortest path in the multiple- weighted graphs to find maximal flow in extended linear multicomodity multicost network

The shortest path finding algorithm is used in many problems on graphs and networks. This article will introduce the algorithm to find the shortest path between two vertices on the extended graph. Next, the algorithm finds the shortest path between the pairs of vertices on the extended graph with mu

A novel 3D skeleton algorithm based on neutrosophic cost function

This paper proposed a novel algorithm to extract the skeleton for the objects on three dimensional images with or without noise.Neutrosophic cost function is proposed based on neutrosophic set.Neutrosophic cost function is employed to define the cost between each point on skeleton. A skeleton provides a synthetic and thin representation of three dimensional objects, and is useful for shape description and recognition. In this paper, a novel 3D skeleton algorithm is proposed based on neutrosophic cost function. Firstly, the distance transform is used to a 3D volume, and the distance matrix is obtained for each voxel in the volume. The ridge points are identified based on their distance transform values and are used as the candidates for the skeleton. Then, a novel cost function, namely neutrosophic cost function (NCF) is proposed based on neutrosophic set, and is utilized to define the cost between each ridge points. Finally, a shortest path finding algorithm is used to identify the optimum path in the 3D volume with least cost, in which the costs of paths are calculated using the new defined NCF. The optimum path is treated as the skeleton of the 3D volume. A variety of experiments have been conducted on different 3D volume. The experimental results demonstrate the better performance of the proposed method. It can identify the skeleton for different volumes with high accuracy. In addition, the proposed method is robust to the noise on the volume. This advantage will lead it to wide application in the skeleton detection applications in the real world.

A Literature review on finding the K Shortest Path using Dynamic Route Guidance Systems

The shortest path problem is one of the most fundamental problems applicable in various fields and has close relation to route navigation systems. This is actually quite an established technique for multi-criteria optimization. A literature review on this technique with focus on transportation network would be quite helpful for any research related to dynamicRoute Guidance systems (RGS). Route guidance helps us in providing the path directions based on changing traffic conditions. Given a set of origin-destination (O/D) pairs, there could be many possible routes for a driver. A useful routing system should have the capability to support the driver effectively in deciding on an optimum route to his preference. The algorithm is suitable for finding not only the shortest route but also better routes. The shortest travel time is estimated by applying various shortest path algorithms to the traffic network that has deterministic or dynamic link travel times. Because it is difficult to evaluate these shortest path-finding algorithms in real traffic situations, most of them are evaluated in the virtual traffic networks. Index terms: Route guidance, Dijkstra Algorithm, Navigation, Fuzzy Neural network.

A novel 3D skeleton algorithm based on neutrosophic cost function

A skeleton provides a synthetic and thin representation of three dimensional objects, and is useful for shape description and recognition. In this paper, a novel 3D skeleton algorithm is proposed based on neutrosophic cost function. Firstly, the distance transform is used to a 3D volume, and the distance matrix is obtained for each voxel in the volume. The ridge points are identified based on their distance transform values and are used as the candidates for the skeleton. Then, a novel cost function, namely neutrosophic cost function (NCF) is proposed based on neutrosophic set, and is utilized to define the cost between each ridge points. Finally, a shortest path finding algorithm is used to identify the optimum path in the 3D volume with least cost, in which the costs of paths are calculated using the new defined NCF. The optimum path is treated as the skeleton of the 3D volume. A variety of experiments have been conducted on different 3D volume. The experimental results demonstrate the better performance of the proposed method. It can identify the skeleton for different volumes with high accuracy. In addition, the proposed method is robust to the noise on the volume. This advantage will lead it to wide application in the skeleton detection applications in the real world.

ROUTE CHOICE MODELLING FOR BICYCLE TRIPS

This paper intends to find out which parameters have the highest influence on bicyclists' route-choice-behaviour and how they contribute. There are many attributes considered throughout different studies that are favoured by cyclists. The attributes are the basis for generating a function which predicts the route choice of cyclists. The paper aims at making a comparison between distance-based routes and attribute-based routes. The model for creating the bicycle route choice program is based on the network model of Norrkoping, Sweden. The preferred attributes of the model each assign a weight in the cost function of the model for each link of the urban network. The algorithm of the lowest cost function route searches the shortest path in terms of assigned link costs over the whole network. For comparing the results of the cost function and the shortest route (between an origin-destination), the model has a shortest path finding algorithm between different Origin and Destination pairs implemented. It has been viewed that around 25% of all cumulative routes do not show any distance differences between the shortest path distance and attributes based solution. With the used weights of the Standard scenario, it can be seen that the trade-off between shortest distance and safety respectively comfort can be optimized, fulfilling both criteria (distance and safety/comfort).

A generalization of Dijkstra's shortest path algorithm with applications to VLSI routing

We generalize Dijkstra's algorithm for finding shortest paths in digraphs with non-negative integral edge lengths. Instead of labeling individual vertices we label subgraphs which partition the given graph. We can achieve much better running times if the number of involved subgraphs is small compared to the order of the original graph and the shortest path problems restricted to these subgraphs is computationally easy.As an application we consider the VLSI routing problem, where we need to find millions of shortest paths in partial grid graphs with billions of vertices. Here, our algorithm can be applied twice, once in a coarse abstraction (where the labeled subgraphs are rectangles), and once in a detailed model (where the labeled subgraphs are intervals). Using the result of the first algorithm to speed up the second one via goal-oriented techniques leads to considerably reduced running time. We illustrate this with a state-of-the-art routing tool on leading-edge industrial chips.

COMBING MULTILEVEL GREEN'S FUNCTION INTERPOLATION METHOD WITH VOLUME LOOP BASES FOR INDUCTANCE EXTRACTION PROBLEMS

In this paper,a fast integral equation method is developed for extracting the inductances in RF ICs,RF MEMs,IC packages,and deep submicron ICs etc. This method combines a recently developed Multilevel Green's Function Interpolation Method (MLGFIM) (1,2) with the volume integral equation discretized using Volume Loop (VL) basis functions. In it,instead of using the filaments model to simulate the currents flowing in the inductors,we use the conventional SWG basis functions for this kind of basis functions is flexible for problems with complex geometries. The shortest path finding algorithm is also used to find the source loop basis functions. The inductance extractions from the straight line,the spiral inductors,the bump,and the parallel buses in this paper demonstrate the validity and efficiency of this hybrid method.

Application of Auction Algorithm for Shortest Paths to Traffic Assignment

Auction algorithm is a new and simple algorithm for finding shortest paths in a directed graph proposed by Prof. Bertsekas, whose application has been extended to solve a variety of linear network flow problems. In this paper, auction algorithm for shortest paths is introduced and its characteristics are analyzed. The paper compares the auction algorithm with other algorithms widely used such as label-setting algorithm and label-correcting algorithm. The auction algorithm is particularly applicable to parallel computation and to the solution of a large-scale sparse network, which precisely meets the requirements of the traffic assignment. The algorithm is easy to program. Through a variety of measures the basic algorithm can be improved and speeded up and the computation speed can be increased by several times. The auction algorithm can be adopted in various traffic assignment methods. It can be used efficiently in the case of multiple origins and a single destination, and a single origin and multiple destinations. Different origin sets and destination sets are determined in accordance with the requirement of the traffic assignment. It is not required any more to find the shortest paths connecting any node pairs, so a lot of computation can be avoided and the computing time can be reduced by the use of the auction algorithm in the traffic assignment. Auction algorithms can thus be broadly applied in the transportation fields.

Planar graphs, negative weight edges, shortest paths, and near linear time

In this paper, we present an O ( n log 3 n ) time algorithm for finding shortest paths in an n-node planar graph with real weights. This can be compared to the best previous strongly polynomial time algorithm developed by Lipton, Rose, and Tarjan in 1978 which runs in O ( n 3 / 2 ) time, and the best polynomial time algorithm developed by Henzinger, Klein, Subramanian, and Rao in 1994 which runs in O ˜ ( n 4 / 3 ) time. We also present significantly improved data structures for reporting distances between pairs of nodes and algorithms for updating the data structures when edge weights change.

Shortest path search using tiles and piecewise linear cost propagation

In this paper we propose a new algorithm for finding shortest paths in a tile connection graph. This algorithm uses an exact piecewise linear cost model to guide our search of the compact tile graph. Unlike previous tile search algorithms, this algorithm always rinds a shortest path. Unlike the grid graph algorithms (which do find shortest paths), this algorithm searches the tile graph which is much smaller than the grid graph. The efficiency of our new approach is confirmed by our experiments comparing our new algorithm with the grid graph algorithms.

A self-stabilizing algorithm for the shortest path problem in a distributed system

In this paper, we propose a self-stabilizing algorithm for finding shortest paths in a distributed system in which a central daemon is assumed. The correctness of the proposed algorithm is proved by using the bounded function technique.