scholarly journals SISTEM PENDUKUNG KEPUTUSAN OTOMATISASI PLANNING WISATA BERBASIS WEBSITE DENGAN MENGGUNAKAN METODE DIJKSTRA

Compiler ◽  
2013 ◽  
Vol 2 (1) ◽  
Author(s):  
Eko Suryanto ◽  
Anton Setiawan Honggowibowo ◽  
Nurcahyani Dewi Retnowati
Keyword(s):  
Shortest Path ◽  
Search Algorithm ◽  
Graph Search ◽  
Single Source ◽  
Application Development ◽  
Tourism Planning ◽  
Shortest Path Tree

The application development of website that have a good progress from Website is very important in tourism field where website can promote the interesting and unique of tourism place for tourist. In tourism field website can be important if completed with superriority is tourism planning where tourist can plan their holidays effective and efficient. Dijkstra method is a graph search algorithm is used to solve the problem with a single source shortest path on a graph that produces a shortest path tree. The usage of dijkstra method in decision the tourism planning base website is appropriate because used to plan the holidays based on the route or the sorthest way that has been found by latitude and longitude counting which is very important to decide range from each place, so it can help the tourist.

scholarly journals Facilitating Large-Scale Graph Search Algorithms with Lock-Free Concurrent Pairing Heaps

2019 ◽  
Author(s):  
Jeremy Mayeres ◽  
Charles Newton ◽  
Helena Arpudaraj
Keyword(s):  
Data Structures ◽  
Shortest Path ◽  
Large Scale ◽  
Search Algorithm ◽  
Search Algorithms ◽  
Graph Search ◽  
Dijkstra’S Algorithm ◽  
Single Source ◽  
Dijkstra's Algorithm ◽  
Graph Search Algorithms

This paper introduces a lock-free version of a Pairing heap. Dijkstra's algorithm is a search algorithm to solve the single-source shortest path problem. The performance of Dijkstra's algorithm improves when threads can also perform work concurrently (in particular, when decreaseKey calls occur concurrently.) However, current implementations of decreaseKey on popular backing data structures such as Pairing heaps and Fibonacci heaps severely limit concurrency. Lock-free techniques can improve the concurrency of search structures such as heaps. In this paper we introduce decreaseKey and insert operators for Pairing heaps that provide lock-free guarantees while still running in constant time.

Single-Source Shortest Path Tree for Big Dynamic Graphs

2018 ◽  
Author(s):  
Sara Riazi ◽  
Sriram Srinivasan ◽  
Sajal K. Das ◽  
Sanjukta Bhowmick ◽  
Boyana Norris
Keyword(s):  
Shortest Path ◽  
Single Source ◽  
Dynamic Graphs ◽  
Shortest Path Tree

scholarly journals A novel genetic algorithm for solving the clustered shortest-path tree problem

2020 ◽  
Vol 36 (3) ◽  
pp. 401-414
Author(s):  
OVIDIU COSMA ◽  
PETRICA C. POP ◽  
IOANA ZELINA
Keyword(s):  
Genetic Algorithm ◽  
Shortest Path ◽  
Spanning Tree ◽  
The Other ◽  
Computational Results ◽  
Single Source ◽  
High Quality ◽  
Shortest Path Tree ◽  
Solution Approach ◽  
Benchmark Instances

The clustered shortest-path tree problem is an extension of the classical single-source shortest-path problem, in which, given a graph with the set of nodes divided into a redefined, mutually exclusive and exhaustive set of clusters, we want to determine a shortest-path spanning tree from a given source to all the other nodes of the graph, with the property that each cluster should induce a connected subtree. The investigated problem proved to be NP-hard and therefore we proposed an efficient genetic algorithm in order to solve it. The preliminary computational results reported on a set of benchmark instances from the literature proved that our proposed solution approach yields high-quality solutions within reasonable running times.

scholarly journals A bi-level encoding scheme for the clustered shortest-path tree problem in multifactorial optimization

2021 ◽  
Vol 100 ◽  
pp. 104187 ◽  
Author(s):  
Huynh Thi Thanh Binh ◽  
Ta Bao Thang ◽  
Nguyen Duc Thai ◽  
Pham Dinh Thanh
Keyword(s):  
Shortest Path ◽  
Shortest Path Tree ◽  
Encoding Scheme

Optimal Robotic Assembly Planning Using Dijkstra’s Algorithm

1994 ◽  
Author(s):  
Sam Anand ◽  
Mohamed Sabri
Keyword(s):  
Configuration Space ◽  
Material Handling ◽  
Search Algorithm ◽  
Robotic Manipulators ◽  
Robotic Assembly ◽  
Graph Search ◽  
Assembly Planning ◽  
Robotic Welding ◽  
Fast Collision ◽  
Space Approach

Abstract Robots play an important role in the modern factory and are used in a manufacturing cell for several functions such as assembly, material handling, robotic welding, etc. One of the principal problems faced by robots while performing their tasks is the presence of obstacles such as fixtures, tools, and objects in the robot workspace. Such objects could result in a collision with one of the arms of the robots. Fast collision-free motion planning algorithms are therefore necessary for robotic manipulators to operate in a wide variety of changing environments. The configuration space approach is one of the widely used methods for collision-free robotic path planning. This paper presents a novel graph-based method of searching the configuration space for a collision-free path in a robotic assembly operation. Dijkstra’s graph search algorithm is used for optimizing the joint displacements of the robot while performing the assembly task. The methodology is illustrated using a simple robotic assembly planning task.

scholarly journals Multitarget Tracking Algorithm Based on Adaptive Network Graph Segmentation in the Presence of Measurement Origin Uncertainty

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3791
Author(s):  
Tianli Ma ◽  
Song Gao ◽  
Chaobo Chen ◽  
Xiaoru Song
Keyword(s):  
Shortest Path ◽  
Clustering Algorithm ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Tracking Algorithm ◽  
Multitarget Tracking ◽  
Integer Programming Problem ◽  
Tracking Accuracy ◽  
Network Graph ◽  
Adaptive Network

To deal with the problem of multitarget tracking with measurement origin uncertainty, the paper presents a multitarget tracking algorithm based on Adaptive Network Graph Segmentation (ANGS). The multitarget tracking is firstly formulated as an Integer Programming problem for finding the maximum a posterior probability in a cost flow network. Then, a network structure is partitioned using an Adaptive Spectral Clustering algorithm based on the Nyström Method. In order to obtain the global optimal solution, the parallel A* search algorithm is used to process each sub-network. Moreover, the trajectory set is extracted by the Track Mosaic technique and Rauch–Tung–Striebel (RTS) smoother. Finally, the simulation results achieved for different clutter intensity indicate that the proposed algorithm has better tracking accuracy and robustness compared with the A* search algorithm, the successive shortest-path (SSP) algorithm and the shortest path faster (SPFA) algorithm.

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