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Timur Keskintürk
Global Karınca Kolonisi Optimizasyonu
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
This paper presents a new metaheuristic approach called Global Ant Colony Optimization (GACO). GACO differs from the other ACO techniques that ants don’t need to visit all nodes or don’t complete the tour. GACO is developed to solve lot sizing problem. GACO is able to find new alternative solution by starting any node and visiting one or more nodes. There is no local pheromone update in GACO. Global pheromone update and ant’s path choice is carried out by using complete path information. GACO has been applied to solve various size of one item LSP. Computer solutions demonstrate that GACO is a good alternative solution method for solving LSP.