GLOBAL KARINCA KOLONİSİ OPTİMİZASYONU

Öz

Bu çalışmada, Global Karınca Kolonisi Algoritması (Global Ant Colony Optimization) (GACO) adı verilen yeni bir karınca kolonisi optimizasyon tekniği anlatılmaktadır. Geliştirilmiş birçok karınca kolonisi optimizasyonu (Ant Colony Optimization) (ACO) sisteminden farklı olarak, karıncaların tam bir tur yapma ya da tüm düğümlere uğrama zorunlulukları yoktur. Özellikle sipariş büyüklüğü problemlerine (Lot Sizing Problem) (LSP) alternatif bir çözüm önerisi olarak geliştirilen GACO’da, herhangi bir düğümden başlayarak ve herhangi bir ya da birden fazla düğüme uğrayarak bir çözüm alternatifi geliştirmek mümkündür. Mevcut ACO’lardan ayrıldığı en temel bir diğer fark ise bölgesel feromon güncellemesinin olmayışıdır. Feromon güncellemesi ve karıncaların yol seçimi yolun tamamı dikkate alınarak gerçekleştirilmektedir. GACO, literatürdeki farklı tip ve boyutlardaki LSP’ne uygulanmıştır. Sonuçlar GACO’nun hem sonuçlar hem de süreler açısından LSP’nin çözümüne iyi bir alternatif olduğunu göstermektedir.

Anahtar Kelimeler

• Karınca kolonisi optimizasyonu, global karınca kolonisi optimizasyonu, sipariş büyüklüğü problemi.

Kaynakça

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