Finding Shortest Paths Research Articles

Coordinated Charging Scheduling of Electric Vehicles: A Mixed-Variable Differential Evolution Approach

The increasing popularity of battery-limited electric vehicles puts forward an important issue of how to charge the vehicles effectively. This problem, commonly referred to as Electric Vehicle Charging Scheduling (EVCS), has been proven to be NP-hard. Most of the existing works formulate the EVCS problem simply as a constrained shortest path finding problem and treat it by discrete optimization. However, other variables such as the charging amount of energy and the charging option at a station need to be considered in practical use. This paper hence formulates the EVCS problem as a hierarchical mixed-variable optimization problem, considering the dependency among the station selection, the charging option at each station and the charging amount settings. To adapt to the new problem model, we specifically design a Mixed-Variable Differentiate Evolution (MVDE) as the scheduling algorithm for our proposed EVCS system. The MVDE contains several specific operators, including a charging station route construction, a hierarchical mixed-variable mutation operator and a constraint-aware evaluation operator. Experimental results validate the effectiveness of our proposed MVDE-based system on both synthetic and real-world transportation networks.

OPTIMIZATION OF EMERGENCY EVACUATION IN FIRE BUILDING BY INTEGRATED BIM AND GIS

Abstract. Building Information Model (BIM) is a database, which makes a detailed 3D geometrical model with rich semantic information of building, go beyond the standard Computer-Aided Design approach. BIM could be as an ideal source to store, formation model and analyses spatial information of internal environments. GIS is an effective tool for analysing the constant and dynamic variables in small areas such as indoor environments. Therefore, integration of the BIM and GIS is useful for integrating the internal environment and networks for designing optimal routes in emergency evacuation problems. Increasing complexity of high-rise buildings and underground structures lead to much more complication in urban disaster management. One of the main challenges in disaster management and emergency evacuation is to guide people in optimal routes to reach safe areas. In this paper, in order to create optimal routes in internal environments and create an internal geometric network model based on the internal nodes and edges, BIM of a 3D commercial building located in the 8th district of Tehran, was made and transferred to the ARCGIS that enables us to use routing algorithms to find the optimize routes between both internal positions. Flammability, occupancy load, width of exit access and distance of fire point criteria were considered to find the safest routes in emergency evacuation times. Network Analysis and Ant Colony's algorithm were applied for finding the safest routes. The results indicated that the Network Analysis was better in terms of processing time and finding short and safe paths related to the Ant Colony's algorithm.

Short chains in circle and in square coverings

The problem of finding short paths avoiding obstacles in a packing was extensively studied. Similar question concerning coverings received less attention. Here we consider locally finite coverings of the plane (i) by discs of radius 1, (ii) by squares of area 1. Given two discs (squares resp.) centered at x and x' one can ask for the least number of discs (squares) needed to connect the given discs (squares resp.). Estimates of type (C + o(1)) d(x,x') as the Euclidean distance d(x,x') rightarrow infty will be given. For discs we prove C= frac{2}{sqrt{3}} thickapprox 1.15 dots , for squares we prove C = 2sqrt{2}. The latter constant turns out to be the best possible.

Data Security and Shortest Path Finding in IOT

Nowadays with the rapid growth of the smart city and the internet of things applications are difficult to connect the data access center, to meet service requirements with low latency and high quality while sending and receiving data access requests. At the same time, lower security performance occurred. In temperature and humidity sensor applications we approach a cryptography technique to protect data. It is an ASCII values-based technique which uses some numerical calculation to perform encryption and decryption. Then the use of the shortest path algorithm we find an entire possible path using current node detail and the destination node is sent by the source node to the neighbourhood nodes. Neighbourhood node receives the detail and checks the destination node. In case, the neighbourhood node is not the destination, it appends its detail along with the received details and sends to its neighbourhood nodes and the process continues till reaching the destination. By calculating the link delay between the two nodes. We can find the delay time taken from source to destination. At last we display the entire possible shortest paths and secure data. It is useful when network congestion occurs. In this paper, we also overcome this problem.

Finding Shortest Paths in a Sequence of Triangles in 3D by the Planar Unfolding

We present an efficient algorithm for finding the shortest path joining two points in a sequence of triangles in three-dimensional space using the concept of funnels associated with common edges along the sequence of triangles and the planar unfolding for each funnel. We show that the unfolded image of a funnel is a simple polygon, it thus is non-overlapping. Therefore, such funnels are determined iteratively to their associated common edges by the planar unfolding and the shortest path joining two points is determined by cusps of these funnels.

The idemetric property: when most distances are (almost) the same.

We introduce the idemetric property, which formalizes the idea that most nodes in a graph have similar distances between them, and which turns out to be quite standard amongst small-world network models. Modulo reasonable sparsity assumptions, we are then able to show that a strong form of idemetricity is actually equivalent to a very weak expander condition (PUMP). This provides a direct way of providing short proofs that small-world network models such as the Watts-Strogatz model are strongly idemetric (for a wide range of parameters), and also provides further evidence that being idemetric is a common property. We then consider how satisfaction of the idemetric property is relevant to algorithm design. For idemetric graphs, we observe, for example, that a single breadth-first search provides a solution to the all-pairs shortest paths problem, so long as one is prepared to accept paths which are of stretch close to 2 with high probability. Since we are able to show that Kleinberg's model is idemetric, these results contrast nicely with the well known negative results of Kleinberg concerning efficient decentralized algorithms for finding short paths: for precisely the same model as Kleinberg's negative results hold, we are able to show that very efficient (and decentralized) algorithms exist if one allows for reasonable preprocessing. For deterministic distributed routing algorithms we are also able to obtain results proving that less routing information is required for idemetric graphs than in the worst case in order to achieve stretch less than 3 with high probability: while Ω(n 2) routing information is required in the worst case for stretch strictly less than 3 on almost all pairs, for idemetric graphs the total routing information required is O(nlog(n)).

Reinforcement Learning Based Stochastic Shortest Path Finding in Wireless Sensor Networks

Many factors influence the connection states between nodes of wireless sensor networks, such as physical distance, and the network load, making the network’s edge length dynamic in abundant scenarios. This dynamic property makes the network essentially form a graph with stochastic edge lengths. In this paper, we study the stochastic shortest path problem on a directional graph with stochastic edge lengths, using reinforcement learning algorithms. we regard each edge length as a random variable following unknown probability distribution and aim to find the stochastic shortest path on this stochastic graph. We evaluate the performance of path-finding algorithms using regret, which represents the cumulative reward difference between the practical path-finding algorithm and the optimal strategy that chooses the global stochastic shortest path every time. We model the path-finding procedure as a Markov decision process and propose two online path-finding algorithms: Q SSP algorithm and SARSA SSP algorithm, both combined with specifically-devised average reward mechanism. We justify the convergence property and correctness of the proposed algorithms theoretically. Experiments conducted on two benchmark graphs illustrate the superior performance of the proposed Q SSP algorithm which outperforms the SARSA SSP algorithm and other competitive algorithms about the regret metric.

New algorithm for digital way-finding map

The purpose of this research was to develop a new algorithm to find the shortest pathfinding that can be implemented on a digital way-finding map. The standard algorithm used for pathfinding is Dijkstra and A*. But for a large search space, the A* and Dijkstra need a large amount of CPU and memory resources. Whereas pathfinding algorithm is usually embedded in devices with limited memory. So, we make the algorithm which requires less memory. In order to make a less memory algorithm, we modify the Breadth First Search (BFS) and Bidirectional Search (BS) algorithm and use the cost graph and modify adjacency matrix. We have tried to reduce the runtime of our algorithm using the modify adjacenvy matrix. The proposed algorithm is then tested for path finding at the institution that has several buildings with many floors where staircase position is not uniform on each floor. The test results were then compared with Djikstra, A*, IDA*, and HPA*. The experiment results showed that our algorithm is faster than the A*, IDA* and Djikstra algorithm. This is because the algorithm that we designed only need to make modify adjacenvy matrix once, so it can reduce the computation time. However, for cases involving multiple floors, our algorithm is not faster than HPA *, but approached. From the test results can be concluded that our algorithm can be implemented in the case of searching the route on buildings that have many floors.

Single-Camera Computer Vision Algorithm for Robot Shortest Path Estimator using morphological structuring element with variable sizes

The robotic challeng of developing and implementing a shortest-path finding algorithm to reach a destination without bumping into obstacles has been tackled in this paper. The proposed algorithm is utilized a single ceiling fixed camera and based on the mask and robot size with different sizes for dilation mask. The implementation has been successfully produced thirty-three computer vision figures and two comparison tables of simulation results by using morphological structuring element with different sizes. This paper’s proposal of optimal path finding algorithm is effeciently save robot energy in reaching targets.

Novel optimization using hierarchical Path finding A* (HPA*) algorithm for strategic gaming setup

In game Industry, the most trending research area is shortest path finding. There are many video games are present who are facing the problem of path finding and there is various algorithms are present to solve this problem. In this paper brief introduction is given in the most using algorithm for path finding and A* algorithm has been proved the best algorithm for resolving the problem of shortest path finding in games. It provides the optimal solution for path finding as compare to other search algorithm. At the start of the paper, brief introduction about the path finding is given. Then the reviews of different search algorithm are presented on the basis of path finding. After that information of A* algorithm and optimization techniques are described. In the last, application and examples how the path finding techniques are used in the game is addressed and future work and conclusion are drawn.

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.

Travel time estimation from sparse floating car data with consistent path inference: A fixed point approach

Estimation of urban network link travel times from sparse floating car data (FCD) usually needs pre-processing, mainly map-matching and path inference for finding the most likely vehicle paths that are consistent with reported locations. Path inference requires a priori assumptions about link travel times; using unrealistic initial link travel times can bias the travel time estimation and subsequent identification of shortest paths. Thus, the combination of path inference and travel time estimation is a joint problem. This paper investigates the sensitivity of estimated travel times, and proposes a fixed point formulation of the simultaneous path inference and travel time estimation problem. The methodology is applied in a case study to estimate travel times from taxi FCD in Stockholm, Sweden. The results show that standard fixed point iterations converge quickly to a solution where input and output travel times are consistent. The solution is robust under different initial travel times assumptions and data sizes. Validation against actual path travel time measurements from the Google API and an instrumented vehicle deployed for this purpose shows that the fixed point algorithm improves shortest path finding. The results highlight the importance of the joint solution of the path inference and travel time estimation problem, in particular for accurate path finding and route optimization.

A COMPARISON OF ARTIFICIAL NEURAL NETWORK AND HOMOTOPY CONTINUATION IN 3D INTERIOR BUILDING MODELLING

Abstract. Indoor surveying is currently based on laser scanning technology, which is time-consuming and costly. A construction model depends on complex calculations which need to manage a large number of measured points. This is suitable for the detailed geometrical models utilized for representation, yet excessively overstated when a simple model including walls, floors, roofs, entryways, and windows is required, such a basic model being a key for efficient network analysis such as shortest path finding. To reduce the time and cost of the indoor building data acquisition process, the Trimble LaserAce 1000 range finder is used. A comparison of neural network and a combined method of interval analysis and homotopy continuation in 3D interior building modelling for calibration of inaccurate surveying equipment is presented. We will present the interval valued homotopy model of the measurement of horizontal angles by the magnetometer component of the rangefinder. This model blends interval analysis and homotopy continuation. The results prove that homotopies give the best results both in terms of RMSE and the L∞ metric.

Shortest Route Optimization for Emergency Service: Case Study in Kumasi, Ghana

It is becoming difficult for emergence services to find the best route especially in Kumasi to any destination in order to save lives in real time. This study deals with the problem of finding shortest paths in traversing some locations within the Kumasi Metropolis in the Ashanti Region of Ghana. Dijkstra‘s Algorithm was selected to determine the shortest distances from any location to any destination within the Kumasi metropolis. The objective of thesis is to use Dijkstra‘s algorithm in constructing the minimum spanning tree considering the dual carriage ways in the road network of Kumasi metropolis within the shortest possible time for emergence services. The distance between 51 locations of the towns with the major roads was measured and a legend and a matrix were formulated. A visual basic program was prepared using Dijkstra‘s algorithm. The distances were used to prepare an input deck for the visual program. The methodology employed included review of relevant literature of the types of Dijkstra‘s algorithm and methods employed in the solution of the Dijkstra‘s algorithm and to develop computer solutions – ArcGIS and VB.net for faster computation of Dijkstra‘s algorithm. The result shows a remarkable reduction in the actual distance as compared with the ordinary routing. These results indicate, clearly the importance of this type of algorithms in the optimization of network flows. Hence the shortest distance from any area in Kumasi metropolis to another can easily be calculated using this thesis so as to minimize the average loss of lives in case emergences.

The Length of Shortest Vertex Paths in Binary Occupancy Grids Compared to Shortest r-Constrained Ones

We study the problem of finding a short path from a start to a goal within a two-dimensional continuous and isotropic terrain that has been discretized into an array of accessible and blocked cells. A classic approach obtains a grid path where each step is along the edge of an accessible cell or diagonally across one. Grid paths suffer from `digitization bias' -- even if two locations have line-of-sight, the minimum travelling cost between them can be greater than the distance along the line-of-sight. In a vertex path, steps are allowed from a cell corner to any other cell corner if they have line-of-sight. While the `digitization bias' is smaller, shortest vertex paths are impractical to find by brute force. Recent research has thus turned to methods for finding short (but not necessarily shortest) vertex paths. To establish the methods' potential utility, we calculate upper bounds on the difference in length between the shortest vertex paths versus the shortest r-constrained ones where an r-constrained path consists of line segments that each traverse at most r rows and at most r columns of cells. The difference in length reduces as r increases -- indeed the shortest vertex paths are at most 1 percent shorter than the shortest 4-constrained ones. This article will be useful to developers and users of short(est) vertex paths algorithms who want to trade path length for improved runtimes in a predictable manner.

Finding Shortest Path Basing on Dijkstra's Algorithm For Baghdad Universities by using Geographic Information System Applications

As the population increases, the transport network becomes difficult and enormous. Finding demanded location is becomes a troublesome task. After finding, a location individual gets confused to access that location because of the routes contains several modes. This drawback is even more substantial for those who may have to go to strange parts of the city. Just in case of the universities, it is troublesome to find the specified university and it's the shortest path to access therefore takes longer to access it. In this paper solved this problem by find the shortest path from the user location to the university or between two universities. The area for study is Baghdad city and the coordinate for universities is obtained from Google earth program. The ArcGIS software system used and also the Dijkstra’s algorithm to produce the shortest path from one location to a different and ArcGIS cloud publisher for publish map from ArcMp to ArcGIS cloud and then can be edited and updated

Shortest Alternate Path Discovery through Recursive Bounding Box Pruning

Congestion is a dynamic phenomenon and hence efficiently computing alternate shortest route can only help expedite decongestion. This research is aimed to efficiently compute shortest path for road traffic network so that congestion can be eased resulting in reduced CO2 emission and improved economy. Congestion detection is achieved after evaluating road capacity and road occupancy. Congestion index, a ratio of road occupancy to road capacity is computed, congestion index higher than 0.6 necessitates computation of alternate shortest route. Various algorithms offer shortest alternate route. The paper discusses minimization of graph based by removing redundant nodes which don’t play a role in computation of shortest path. The proposal is based on continuous definition of a bounding box every time a next neighboring node is considered. This reduces maximum number of contentious nodes repeatedly and optimizes the network. The algorithm is deployed from both the ends sequentially to ensure zero error and validate the shortest path discovery. While discovering shortest path, the algorithm also offers an array of shortest path in ascending order of the path length. However, vehicular traffic exhibits network duality viz. static and dynamic network graphs. Shortest route for static distance graph is pre-computed and stored for look-up, alternate shortest path based on assignment of congestion levels to edge weights is triggered by congestion index. The research also supports directed graphs to address traffic rules for lanes having unidirectional and bidirectional traffic.