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    Wyświetlanie 1-5 z 5
    Tytuł:
    Emergency Evacuation Route Choice Based on Improved Ant Colony Algorithm
    Autorzy:
    Wang, Bo
    Zhou, Ling Bo Jibiao
    Hu, Danjuan
    Pawęska, Marcin
    Šimák, Ladislav
    Ristvej, Jozef
    Jánošíková, Michaela
    Powiązania:
    https://bibliotekanauki.pl/articles/503788.pdf
    Data publikacji:
    2019
    Wydawca:
    Międzynarodowa Wyższa Szkoła Logistyki i Transportu
    Tematy:
    route choice
    ant colony algorithm
    brittleness
    emergency evacuation
    Opis:
    In order to explore the optimal route choice for emergency evacuation in the campus, we propose a novel route choice method based on brittle characteristics of campus system and improved ant colony algorithm. Both optimal and worst-case emergency evacuation routes are simulated in the campus of Ningbo University of Technology. From the simulation, the length of optimal and worse-case evacuation routes between the starting point and eight exits can be obtained by adjusting the importance value of trip distance and the degree of conformity, under the condition of static relative importance of pheromone concentration to graph G. The optimal route of emergency evacuation in the campus can be obtained when the importance of trip distance is above 5 and the degree of conformity is above 0.3; while the worse-case route is obtained with the importance of trip distance above 5 and the degree of conformity below 0.5.
    Źródło:
    Logistics and Transport; 2019, 44, 4; 33-39
    1734-2015
    Pojawia się w:
    Logistics and Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Research on optimization model of marine industry strategic adjustment under complex maritime conditions based on ant colony algorithm
    Autorzy:
    Shen, X.
    Powiązania:
    https://bibliotekanauki.pl/articles/260022.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    ant colony algorithm
    complex maritime
    marine industry strategy
    Opis:
    This article seeks to analyze the factors constraining the development of strategic marine emerging industries and the deficiencies in China’s strategic marine emerging industry development policies. Learn from the successful experiences of overseas strategic marine emerging industry development policies. We will study and construct a policy framework for the development of strategic marine emerging industries in the new era, guided by the scientific concept of development and enhanced by the capacity of independent innovation. Provide policy recommendations for actively promoting the development of strategic marine emerging industries. At the same time, it provides theoretical and methodological reference for the formulation and implementation of China’s strategic marine emerging industry policies. On the basis of reviewing relevant theories of industrial policy, this article first defines China’s strategic emerging industries and clarifies the connotation of China’s strategic marine emerging industry development policies. Then, the paper conducts detailed analysis on the development policies of strategic marine emerging industries at home and abroad, and summarizes the experience of overseas strategic development policies for marine emerging industries. Finally, combining the above-mentioned comprehensive analysis, with the guidance of the scientific concept of development, the development strategy and concrete development policy of China’s strategic emerging industries in the ocean are proposed.
    Źródło:
    Polish Maritime Research; 2018, S 2; 164-169
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A hybrid algorithm based on non-dominated sorting ant colony and genetic algorithmsfor solving multi-objective multi-mode project scheduling problems under resource constraints
    Autorzy:
    Bagherinejad, Jafar
    Jolai, Fariborz
    Abdollahnejad, Raheleh
    Shoeib, Mahnaz
    Powiązania:
    https://bibliotekanauki.pl/articles/407427.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    multi-objectives project scheduling
    ant colony algorithm
    time-cost trade-off
    resource leveling
    Opis:
    A project scheduling problem investigates a set of activities that have to be scheduled due to precedence priority and resource constraints in order to optimize project-related objective functions. This paper focuses on the multi-mode project scheduling problem concerning resource constraints (MRCPSP). Resource allocation and leveling, renewable and non-renewable resources, and time-cost trade-off are some essential characteristics which are considered in the proposed multi-objective scheduling problem. In this paper, a novel hybrid algorithm is proposed based on non-dominated sorting ant colony optimization and genetic algorithm (NSACO-GA). It uses the genetic algorithm as a local search strategy in order to improve the efficiency of the ant colony algorithm. The test problems are generated based on the project scheduling problem library (PSPLIB) to compare the efficiency of the proposed algorithm with the non-dominated sorting genetic algorithm (NSGA-II). The numerical result verifies the efficiency of the proposed hybrid algorithm in comparison to the NSGA-II algorithm.
    Źródło:
    Management and Production Engineering Review; 2020, 11, 2; 88-98
    2080-8208
    2082-1344
    Pojawia się w:
    Management and Production Engineering Review
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Comparative Study of PID Controller Tuning Using GA, EP, PSO and ACO
    Autorzy:
    Nagaraj, B.
    Vijayakumar, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/384767.pdf
    Data publikacji:
    2011
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    ant colony algorithm
    evolutionary program
    genetic algorithm particle swarm optimization and soft computing
    Opis:
    Proportional - Integral - Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. How ever PID controller are poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This article comes up with a hybrid approach involving Genetic Algorithm (GA), Evolutionary Pro gramming (EP), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). The proposed hybrid algorithm is used to tune the PID parameters and its per formance has been compared with the conventional me thods like Ziegler Nichols and Cohen Coon method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. Speed control of DC motor process is used to assess the efficacy of the heuristic algorithm methodology
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2011, 5, 2; 42-48
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Ship route planning using historical trajectories derived from AIS Data
    Autorzy:
    He, Y. K.
    Zhang, D.
    Zhang, J. F.
    Zhang, M. Y.
    Li, T. W.
    Powiązania:
    https://bibliotekanauki.pl/articles/116536.pdf
    Data publikacji:
    2019
    Wydawca:
    Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
    Tematy:
    AIS Data
    Automatic Identification System (AIS)
    route planning
    historical trajectories
    AIS messages
    marine traffic
    Dijkstra algorithm
    ant colony algorithm
    Opis:
    Ship route planning is one of the key issues in enhancing traffic safety and efficiency. Many route planning methods have been developed, but most of them are based on the information from charts. This paper proposes a method to generate shipping routes based on historical ship tracks. The ship's historical route information was obtained by processing the AIS data. From which the ship turning point was extracted and clustered as nodes. The ant colony algorithm was used to generate the optimize route. The ship AIS data of the Three Gorges dam area was selected as a case study. The ships’ optimized route was generated, and further compared with the actual ship's navigation trajectory. The results indicate that there is space of improvement for some of the trajectories, especially near the turning areas.
    Źródło:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2019, 13, 1; 69-76
    2083-6473
    2083-6481
    Pojawia się w:
    TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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