A binary enhanced moth flame optimization algorithm for uncapacitated facility location problems

Authors : Ahmet Özkiş, Murat Karakoyun

Pages : 737-751

View : 63 | Download : 55

Publication Date : 2023-12-30

Article Type : Research Paper

Abstract :Moth Flame Optimization is a nature-inspired meta-heuristic algorithm for constantly solving real-world problems. In this study, a modified version of MFO called binary Enhanced MFO Desert Bush (binEMFO-DB) algorithm is proposed to solve uncapacitated facility location problems. The proposed algorithm includes three modifications: i) chaotic mapbased population initialization, ii) random flame selection, and iii) desert bush strategy. The performance of the proposed binEMFO-DB algorithm was tested on 15 different UFL problems from the OR-Library and Taguchi orthogonal array design was used for parameter analysis. The average, gap and hit values of the results obtained by the algorithms were used as performance metrics. The performance of binEMFO-DB is compared with the performance of state-of-the-art algorithms. The results show that the proposed binEMFO-DB has a successful and competitive performance in the test environment.
Keywords : Güve alevi optimizasyonu, Kapasitesiz tesis yerleşim problemi, İkili optimizasyon, Çöl çalısı, Transfer fonksiyonları, Taguchi