Hybrid flower pollination algorithm approach for the two-dimensional bin packing problem Iki boyutlu kutu paketleme probleminin çözümü için hibrit çiçek tozlaşma algoritmasi yaklaşimi
Journal of the Faculty of Engineering and Architecture of Gazi University, cilt.37, sa.3, ss.1523-1534, 2022 (SCI-Expanded, Scopus, TRDizin)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 37 Sayı: 3
- Basım Tarihi: 2022
- Doi Numarası: 10.17341/gazimmfd.764853
- Dergi Adı: Journal of the Faculty of Engineering and Architecture of Gazi University
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Art Source, Compendex, TR DİZİN (ULAKBİM)
- Sayfa Sayıları: ss.1523-1534
- Anahtar Kelimeler: Bin packing problem, Flower pollination algorithm, Genetic algorithm, Combinatorial optimization, Hybridization
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Kırklareli Üniversitesi Adresli: Evet
Özet
Two-dimensional bin packing problem (2DBPP) is a sub-branch of cutting and packaging problems (CPP). Researchers often use meta-heuristic algorithms in the solution of 2DBPP, because in cases where a large number of samples exist, meta-heuristic algorithms reach acceptable solutions in reasonable time. In this article, a novel hybrid meta-heuristic algorithm is proposed for the solution of 2DBPP. The proposed algorithm combines flower pollination algorithm (FPA) and genetic algorithm (GA). In order to improve FPA's global search capability, FPA's local search operator is modified. The proposed algorithm has been compared to six recently published meta-heuristic algorithms. For comparison, a data set containing 10 classes, 50 subgroups and 500 samples was used. Average container values of each class and of each subgroup were used as comparison parameters. In addition, Friedman test was used to evaluate the relative performance of the algorithms. The proposed algorithm achieved the most successful results in 6 of the 10 classes of the data set and 33 of the 50 subgroups. In the Friedman test, it was the most successful algorithm with a score of 2.6. The results confirm the validity of the proposed meta-heuristic algorithm.