Solution Of Order Batching Problem With Association Rules And Genetic Algorithm: A Case Study In Pharmacy Warehouse


Furkan Yener
Res. Asst., Sakarya University, Sakarya, Turkey, fyener@sakarya.edu.tr

Harun Reşit Yazgan
Assoc. Prof., Sakarya University, Sakarya, Turkey, yazgan@sakarya.edu.tr

Serap Ercan Cömert
Res. Asst., Sakarya University, Sakarya, Turkey, serape@sakarya.edu.tr

Sena Kır
Res. Asst., Sakarya University, Sakarya, Turkey, senas@sakarya.edu.tr

Yağmur Kaya
B.Sc., Sakarya University, Sakarya, Turkey, ygmr-kaya@hotmail.com

Abstract

In this study, daily strategy of order picking is examined and proposed a new approach in a pharmacy warehouse. If the goods and orders are relatively small for the picker’s capacity, the order batching strategy should put to use. Daily orders was divided to order batches using mathematical model maximised the relationship among the orders. The order batches which are consist of more than one orders save up time and distance during the order picking period. Optimum solution of mathematical model take up time so that Genetic algorithm is used for order batching problem. Travelled the total distance is simulated in existing and batching strategy, the confidingness and performance of the results are tested statistically and argued in conclusion.

Keywords: Warehouse management, Data mining, Genetic algorithm, Order batching

Birliktelik Kuralları ve Genetik Algoritma İle Sipariş Yığınlama Probleminin Çözümü: Bir Ecza Deposunda Uygulama


Öz

Bu çalışmada, bir ecza deposunun günlük sipariş toplama stratejisi incelenmiş ve uygun bir yaklaşım geliştirilmiştir. Ürünlerin ve siparişlerin hacimsel olarak küçük olduğu, toplayıcı kapasitesinin göreceli olarak büyük olduğu depolar için uygun olan, sipariş yığınlama stratejisi kullanılmıştır. Günlük siparişler, siparişler arası ilişkiyi en büyükleyen bir matematiksel modelin yardımıyla sipariş yığınlarına ayrılmış. Birden çok siparişin bir araya gelmesiyle oluşan yığınlar içerisinde benzer ürünleri içeren siparişler bulunduğu için toplama sırasında ki kayıp zaman ve mesafeden tasarruf sağlanacaktır. Matematiksel modelin kesin çözümünün zaman alması nedeniyle genetik algoritma kullanılarak sonuç üretilmiştir. Farklı toplama stratejileri sonucunda kat edilen toplam mesafe benzetim yardımıyla hesaplanarak, istatistiki olarak sonuçların güvenilirliği ve performansları sonuç bölümünde tartışılmıştır.

Anahtar Kelimeler: Depo yönetimi, Veri madenciliği, Genetik algoritma, Sipariş yığınlama


Cite this article

Yener, F., Yazgan, HR., Ercan Cömert, S., Kır, S., Kaya, Y. (2016). Birliktelik Kuralları ve Genetik Algoritma İle Sipariş Yığınlama Probleminin Çözümü: Bir Ecza Deposunda Uygulama. Journal of Transportation and Logistics, 1(2), 129-142. http://dx.doi.org/10.22532/jtl.267841

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Volume 1, Issue 2, 2016

Journal of Transportation and Logistics

Volume 1, Issue 2, 2016

Pages 129-142

Received: Oct. 10, 2016

Accepted: Oct. 28, 2016

Published: Oct. 31, 2016

Full Text [648.6 KB]

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence Attribution-Non Commercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0).

Istanbul University Press, 2016.