Arama Sonuçları

Listeleniyor 1 - 2 / 2
  • Yayın
    An hybrid approach to solve traveling salesman problem using genetic algorithm
    (Işık Üniversitesi, 2014) Asmazoğlu, Cengiz; Yıldız, Olcay Taner; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Bilgisayar Mühendisliği Yüksek Lisans Programı
    TSP is a challenging and popular problem from combinatorial optimization. TSP is often tackled with well known heuristic genetic algorithm. Due to the nature of the TSP, traditional GA's stay poor when competing with other approaches. Traditional crossover and mutation operators do not satisfy TSP needs. These operators mostly end up with illegal tours. For this reason, researchers proposed many adaptive elements and cooperation of other algorithms. When the logic of GA is combined with these elements, high quality solutions both in time and path length are obtained. In this research, we analyze successful elements from the literature to use them efficiently in a novel algorithm. We also propose a new selection method which works well with our operators. We extend the abilities of greedy crossover and untwist local operator to utilize in our hybrid approach. Multiple populations collaborate together to achieve better solutions. According to the experimental results, proposed novel elements outperforms their counterparts in the TSP literature. Multiple population approach provides better quality solutions.
  • Yayın
    A multilayer annotated corpus for Turkish
    (IEEE, 2018-06-06) Yıldız, Olcay Taner; Ak, Koray; Ercan, Gökhan; Topsakal, Ozan; Asmazoğlu, Cengiz
    In this paper, we present the first multilayer annotated corpus for Turkish, which is a low-resourced agglutinative language. Our dataset consists of 9,600 sentences translated from the Penn Treebank Corpus. Annotated layers contain syntactic and semantic information including morphological disambiguation of words, named entity annotation, shallow parse, sense annotation, and semantic role label annotation.