Sipariş toplama sıklığı düşünceleri altında veri güdümlü depolama yeri atama problemi: Sezgisel bir yaklaşım

Year 2021, Volume: 27 Issue: 4, 520 - 531, 20.08.2021

İpek Çobanoğlu İrem Güre Vedat Bayram

Abstract

Depolama alanları tedarik zinciri yönetiminde kritik öneme sahiptir. Ürün dağıtımı yapmak ve ürünleri depolamak maksadıyla kullanılırlar. Bu çalışmada, bir imalat firması tarafından yönetilen bir depolama alanının depolama yeri ataması kararları optimize edilmiştir. Depo yönetim sistemi tarafından kaydedilen tarihsel verileri kullanarak doğrusal olmayan karışık tam sayılı bir problem, yani depolama alanı atama problemini çözmek için bir matematiksel model sunulmuştur. İki ürünün beraber toplanma sıklığı ve her ürünün toplanma sıklığını baz alarak sırasıyla kümeleme ve ABC analizi yapılmıştır ve sonuçlar matematiksel modele yerleştirilmiştir. Aynı zamanda, firmanın depolama yeri problemini çözmek için açgözlü algoritma geliştirilmiştir. Elde edilen bulgular ışığında, mevcut sistem ve önerilen sistemin G/Ç noktasına olan mesafelerinin karşılaştırılması yapılmış, %49.99’a varan iyileşme görülmüştür.

Keywords

Depolama yeri ataması, Ürün toplama, K-Ortalamalar kümelemesi, ABC analizi, Karışık tam sayılı karesel optimizasyon, Aç gözlü sezgisel

Data driven storage location assignment problem considering order picking frequencies: A heuristic approach

Abstract

Warehouses are crucial in supply chain management. They are used to distribute and store products. In this study, we optimize storage location assignment decisions in a warehouse managed by a manufacturing firm. A mathematical model is introduced to solve the nonlinear mixed integer optimization problem (NLMIP), i.e., the Storage Location Assignment Problem (SLAP) by using historical data from warehouse management system (WMS). Clustering and ABC analysis are conducted based on the number of times two items are picked together and the picking frequency of items, respectively and results are embedded into our optimization model. Also, a greedy heuristic is developed to solve SLAP of the firm. Analysis results show that there is an improvement of up to 49.99% in total distances between filled slots and the I/O point due to proposed solution compared to that of the current system.

Keywords

Storage location assignment, Order picking, K-Means clustering, ABC analysis, Mixed integer quadratic optimization, Greedy heuristic

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