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    Tytuł:
    Ship Collision Avoidance by Distributed Tabu Search
    Autorzy:
    Kim, D.
    Hirayama, K.
    Okimoto, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/116919.pdf
    Data publikacji:
    2015
    Wydawca:
    Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
    Tematy:
    Safety of Navigation
    Collision Avoidance
    Distributed Tabu Search Algorithm (DTSA)
    Distributed Local Search Algorithm (DLSA)
    Quasi-Local Minimum (QLM)
    Tabu Search Algorithm
    Local Search Algorithm
    Distributed Tabu Search
    Opis:
    More than 90% of world trade is transported by sea. The size and speed of ships is rapidly increasing in order to boost economic efficiency. If ships collide, the damage and cost can be astronomical. It is very difficult for officers to ascertain routes that will avoid collisions, especially when multiple ships travel the same waters. There are several ways to prevent ship collisions, such as lookouts, radar, and VHF radio. More advanced methodologies, such as ship domain, fuzzy theory, and genetic algorithm, have been proposed. These methods work well in one-on-one situations, but are more difficult to apply in multiple-ship situations. Therefore, we proposed the Distributed Local Search Algorithm (DLSA) to avoid ship collisions as a precedent study. DLSA is a distributed algorithm in which multiple ships communicate with each other within a certain area. DLSA computes collision risk based on the information received from neighboring ships. However, DLSA suffers from Quasi-Local Minimum (QLM), which prevents a ship from changing course even when a collision risk arises. In our study, we developed the Distributed Tabu Search Algorithm (DTSA). DTSA uses a tabu list to escape from QLM that also exploits a modified cost function and enlarged domain of next-intended courses to increase its efficiency. We conducted experiments to compare the performance of DLSA and DTSA. The results showed that DTSA outperformed DLSA.
    Źródło:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2015, 9, 1; 23-29
    2083-6473
    2083-6481
    Pojawia się w:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Cluster Based Optimization of Routing in Distributed Sensor Networks Using Bayesian Networks with Tabu Search
    Autorzy:
    Bhajantri, L. B.
    Nalini, N.
    Powiązania:
    https://bibliotekanauki.pl/articles/226310.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Distributed Sensor Networks
    routing
    cluster head
    Bayesian Network
    tabu search
    Opis:
    Distributed Sensor Networks (DSNs) have attracted significant attention over the past few years. A growing list of many applications can employ DSNs for increased effectiveness especially in hostile and remote are as. In all application salargen umber of sensors are expected and requiring careful architecture and management of the net work. Grouping nodes in toclusters has been the most popular approach for support scalability in DSN. This paper proposes acluster based optimization of routing in DSN by employing a Bayesi an network (BN) with Tabu search (TS) approach. BN based approach is used to select efficient cluster head sand construction of BN for the proposed scheme. This approach in corporates energy level of each node, band width and link efficiency. The optimization of routing is considered as a design issue in DSN due to lack of energy consumption, delay and maximum time required for data transmission between source nodes (cluster heads) to sink node. In this work optimization of routing takes place through cluster head nodes by using TS. Simulations have been conducted to compare the performance of the proposed approach with LEACH protocol. The objective of the proposed work is to improve the performance of network in terms of energy consumption, through put, packet delivery ratio, and time efficiency of optimization of routing. The results hows that the proposed approach perform better than LEACH protocol that utilizes minimum energy, latency for cluster formation and reduce over head of the protocol.
    Źródło:
    International Journal of Electronics and Telecommunications; 2014, 60, 2; 199-208
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Heuristic algorithms for joint optimization of unicast and anycast traffic in elastic optical network-based large-scale computing systems
    Autorzy:
    Markowski, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/330713.pdf
    Data publikacji:
    2017
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    elastic optical network
    joint optimization
    distributed data center
    metaheuristic algorithm
    tabu search
    elastyczna sieć optyczna
    optymalizacja wspólna
    baza danych rozproszona
    algorytm heurystyczny
    metoda tabu search
    Opis:
    In recent years elastic optical networks have been perceived as a prospective choice for future optical networks due to better adjustment and utilization of optical resources than is the case with traditional wavelength division multiplexing networks. In the paper we investigate the elastic architecture as the communication network for distributed data centers. We address the problems of optimization of routing and spectrum assignment for large-scale computing systems based on an elastic optical architecture; particularly, we concentrate on anycast user to data center traffic optimization. We assume that computational resources of data centers are limited. For this offline problems we formulate the integer linear programming model and propose a few heuristics, including a meta-heuristic algorithm based on a tabu search method. We report computational results, presenting the quality of approximate solutions and efficiency of the proposed heuristics, and we also analyze and compare some data center allocation scenarios.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2017, 27, 3; 605-622
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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