Gazi Journal of Economics and Business

2548-0162

Aydın KARAPINAR

Business Administration

İşletme

KAPASİTE KISITLI STOKASTİK STOK PROBLEMİİÇİN BENZETİMSEL DİNAMİK PROGRAMLAMA SEZGİSELİ

AN APPROXIMATE DYNAMIC PROGRAMMING HEURISTIC FOR THE CAPACITATED STOCHASTIC INVENTORY PROBLEM

Çimen

Mustafa

Belbağ

Sedat

Soysal

Mehmet

02 17 2016

2 1 43 64 02 17 2016

2015

Gazi Journal of Economics and Business

Rekabetçi bir ortamda faaliyet gösteren işletmeler için belirsizlik altında stok yönetimioldukça önemlidir. Bu çalışma kapasite kısıtlı stokastik stok problemine Benzetimsel DinamikProgramlama (Approximate Dynamic Programming‐ADP) tabanlı bir sezgisel yöntemönermektedir. Önerilen sezgisel yöntem, Geçici Farklarla Öğrenme (Temporal DifferenceLearning‐TD) yöntemini kullanmaktadır. Söz konusu problem için sezgisel yöntemden elde edilençözümlerin performansı, Dinamik Programlama algoritmasından elde edilen optimal sonuçlar ilekarşılaştırılarak değerlendirilmiştir. Sayısal örnekler sonucunda ADP’nin kısa süre içerisinde ümitvadeden sonuçlar verdiği gözlenmiştir.

Inventory management under uncertainty is crucial for enterprises operating in competitive environment. This study presents a heuristic based on Approximate Dynamic Programming for the capacitated stochastic inventory problem. The proposed heuristic employs Temporal Difference Learning method. The performance of the heuristic solutions for the aforementioned problem has been assessed relative to the optimal solutions obtained through Dynamic Programming algorithm. Numerical experiments show that Approximate Dynamic Programming provides promising solutions within relatively short computational times.

Stokastik Stok Problemi Kapasite Kısıtı Dinamik Programlama Sezgisel Benzetimsel Dinamik Programlama

Stochastic Inventory Problem Capacity Constraint Dynamic Programming Heuristic Approximate Dynamic Programming

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