The Experts below are selected from a list of 4311 Experts worldwide ranked by ideXlab platform

Toly Chen - One of the best experts on this subject based on the ideXlab platform.

  • a ubiquitous manufacturing network system
    Robotics and Computer-integrated Manufacturing, 2017
    Co-Authors: Toly Chen
    Abstract:

    In this study, a ubiquitous manufacturing network system was constructed. In this system, a customer places an order for an action figure by using a client-side app or a Web-based interface and pays online. The system server then assigns the order to the convenience store nearest the customer's location to print the required action figure. For determining the most suitable convenience store, a fuzzy integer-nonlinear programming model was proposed and solved using two modified fuzzy Dijkstra Algorithms. Subsequently, the customer is informed of the location of and route to the recommended convenience store. Two illustrative cases were used to verify the applicability of using the proposed methodology. In addition, compared with an existing mobile guide, the proposed methodology effectively recommended the shortest path for obtaining the required action figure and reduced the waiting time at the convenience store. We construct a ubiquitous manufacturing network system.A customer places an order for an action figure and pays online.The order is assigned to a convenience store nearest to the customer's location.A fuzzy integer nonlinear programming model is solved to determine the most suitable convenience store.

Alexander Agudelo Acevedo - One of the best experts on this subject based on the ideXlab platform.

  • Voracious and Heuristic Algorithms: A focus on the Minimum Path Problem
    'Corporation Universidad de la Costa CUC', 2020
    Co-Authors: Luis Adrián Lasso Cardona, Diego Fernando Franco Ocampo, Alexander Agudelo Acevedo
    Abstract:

    Introduction: The problem of the shortest route or minimum cost route, has been one of the topics most studied by areas of knowledge such as Operations Research, Computer Science and Decision, Telecommunications, Plant Distribution, Planning of Projects, among others, searching, for example; optimize and reduce the costs that represent the distribution of goods, obtain the minimum amount of time necessary to complete a project, or calculate the shortest possible route between computers connected to a network. Objective: We will study the behavior of three voracious Algorithms that allow us to calculate the minimum cost route between two points (initial state and objective state) in a weighted graph and with heuristics. Method: Was implemented in Java, and the Greedy, A* and Dijkstra Algorithms were adjusted to the problem in question. Subsequently, two instance cases were designed, one negative and one positive. Results: In the negative instance results the heuristic of the node was modified to allow the selected algorithm to escape from local optima and thus obtain a complete result, that is to say reach the objective state, which, in some cases, will not necessarily be the most optimal result. Conclusions: By comparing the three Algorithms, it was determined that the Dijkstra algorithm always yields complete and optimal results. For its part, Greedy and A *, need heuristics to reach a complete result, but not optimal

G Mahinthakumar - One of the best experts on this subject based on the ideXlab platform.

  • finding all pairs shortest path for a large scale transportation network using parallel floyd warshall and parallel Dijkstra Algorithms
    Journal of Computing in Civil Engineering, 2013
    Co-Authors: Anu Pradhan, G Mahinthakumar
    Abstract:

    AbstractParallel computing has become a powerful approach for solving real-time decisions about large-scale, computing-intensive transportation problems. A frequently encountered transportation problem is the “shortest path problem;” that is, finding the shortest path between any two nodes in a transportation network. For the large transportation networks encountered in major metropolitan areas, this problem can be computationally demanding, especially if shortest paths between all the nodes in the network need to be dynamically updated (e.g., evolving traffic conditions). In such a situation, one may wish to harness parallel computing to solve this problem. However, the parallel implementations of commonly used shortest-path Algorithms are computationally demanding because of the inherent sequential nature of the search process used by the Algorithms. This paper describes parallel implementations and includes performance analyses of two prominent graph Algorithms (i.e., Floyd-Warshall and Dijkstra) used ...

Agudelo Acevedo Alexander - One of the best experts on this subject based on the ideXlab platform.

  • Voracious and Heuristic Algorithms: A focus on the Minimum Path Problem
    'Corporation Universidad de la Costa CUC', 2020
    Co-Authors: Lasso Cardona, Luis Adrián, Franco Ocampo, Diego Fernando, Agudelo Acevedo Alexander
    Abstract:

    Introducción: El problema de la ruta más corta o ruta de mínimo costo, ha sido uno de los temas más estudiados por áreas del conocimiento como la Investigación de Operaciones, la Ciencias de la Computación y la Decisión, las Telecomunicaciones, la Distribución en Planta, la Planeación de Proyectos, entre otras, buscando, por ejemplo; optimizar y reducir los costos que representan la distribución de mercancías, obtener la mínima cantidad de tiempo necesaria para finalizar un proyecto, o calcular la ruta más corta posible entre ordenadores conectados a una red. Objetivo: Estudiar el comportamiento de tres algoritmos voraces que permiten calcular la ruta de mínimo costo entre dos puntos (estado inicial y estado objetivo) en un grafo ponderado y con heurísticas. Metodología: Se implementó una aplicación en Java, y se ajustaron los algoritmos Greedy, A* y Dijkstra al problema en cuestión. Posteriormente se diseñaron dos casos de instancia, una negativa y otra positiva. Resultados: En los resultados de instancia negativa se modificó la heurística del nodo para permitir al algoritmo seleccionado escapar de óptimos locales y así, obtener un resultado completo, es decir llegar al estado objetivo, que, en algunas ocasiones, no necesariamente será el resultado más óptimo. Conclusiones: Mediante la comparación entre los tres algoritmos se pudo determinar que el algoritmo de Dijkstra siempre arroja resultados completos y óptimos. Por su parte, Greedy y A*, necesitan de heurísticas para llegar a un resultado completo, pero no óptimo.Introduction: The problem of the shortest route or minimum cost route, has been one of the topics most studied by areas of knowledge such as Operations Research, Computer Science and Decision, Telecommunications, Plant Distribution, Planning of Projects, among others, searching, for example; optimize and reduce the costs that represent the distribution of goods, obtain the minimum amount of time necessary to complete a project, or calculate the shortest possible route between computers connected to a network. Objective: We will study the behavior of three voracious Algorithms that allow us to calculate the minimum cost route between two points (initial state and objective state) in a weighted graph and with heuristics. Method: Was implemented in Java, and the Greedy, A* and Dijkstra Algorithms were adjusted to the problem in question. Subsequently, two instance cases were designed, one negative and one positive. Results: In the negative instance results the heuristic of the node was modified to allow the selected algorithm to escape from local optima and thus obtain a complete result, that is to say reach the objective state, which, in some cases, will not necessarily be the most optimal result. Conclusions: By comparing the three Algorithms, it was determined that the Dijkstra algorithm always yields complete and optimal results. For its part, Greedy and A *, need heuristics to reach a complete result, but not optimal

Syahputra Dinur - One of the best experts on this subject based on the ideXlab platform.

  • Greedy, A-Star, and Dijkstra’s Algorithms in Finding Shortest Path
    'Jurnal Komuniksi ISKI', 2021
    Co-Authors: Wayahdi, Muhammad Rhifky, Ginting, Subhan Hafiz Nanda, Syahputra Dinur
    Abstract:

    The problem of finding the shortest path from a path or graph has been quite widely discussed. There are also many Algorithms that are the solution to this problem. The purpose of this study is to analyze the Greedy, A-Star, and Dijkstra Algorithms in the process of finding the shortest path. The author wants to compare the effectiveness of the three Algorithms in the process of finding the shortest path in a path or graph. From the results of the research conducted, the author can conclude that the Greedy, A-Star, and Dijkstra Algorithms can be a solution in determining the shortest path in a path or graph with different results. The Greedy algorithm is fast in finding solutions but tends not to find the optimal solution. While the A-Star algorithm tends to be better than the Greedy algorithm, but the path or graph must have complex data. Meanwhile, Dijkstra's algorithm in this case is better than the other two Algorithms because it always gets optimal results