Safak KIRIS, DERYA DELİKTAŞ, ÖZDEN ÜSTÜN

İki Amaçlı Genetik Algoritma Yaklaşımı ile Bir Depoda Sipariş Toplama Problemi: Vaka Çalışması

Bu çalışmada, toplam uzaklık ve cezalı erkenlik/gecikme durumlarını dikkate alan bir depoda kapasiteli forklift ile bir sipariş toplama problemi çalışılmıştır. Bu amaçlar, ulaşım maliyetlerini azaltmak ve müşteri beklentilerini karşılamak için önemlidir. Bu problem NP-zor olarak bilindiğinden iki amaçlı sipariş toplama problem çözümü için bir genetik algoritma önerilmiştir. Önerilen yaklaşım, araçtaki tüm elektriksel fonksiyonların çalışmasını sağlayan kablo demetleri üreten bir oto bileşenleri endüstrisine uygulanmıştır. Önerilen GA’nın etkili parametreleri için deney tasarımı kullanılmıştır. GA yaklaşımı ağırlıklı toplam skalerleştirme yöntemi ile çözülmüştür

Anahtar Kelimeler:

Deney tasarımı, Genetik Algoritma, Sipariş toplama, Ağırlıklı toplam skalerleştirme yöntemi

Order Picking Problem in a Warehouse with Bi-Objective Genetic Algorithm Approach: Case Study

In this paper, an order picking problem with the capacitated forklift in a warehouse is studied by considering the total distance and the penalized earliness/tardiness. These objectives are important to reduce transportation costs and to satisfy customer expectations. Since this problem has been known as NP-hard, a genetic algorithm GA is proposed to solve the bi-objective order picking problem. The proposed approach is applied to auto components industry that produces wire harnesses responsible for all electrical functions in the vehicle. Experimental design is used for tuning the influential parameters of the proposed GA. The GA approach was solved by weighted sum scalarization.

Keywords:

Experimental design, Genetic algorithm, Order picking, weighted sum scalarization,

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