Heuristic methods for the stochastic lot-sizing problem under the static-dynamic uncertainty strategy

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Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2013

Öğrenci: ALİ CEM RANDA

Danışman: CEM İYİGÜN

Özet:

We consider a lot-sizing problem in a single-item single-stage production system facing nonstationary stochastic demand in a finite planning horizon. Motivated by practice, the set-up times need to be determined and frozen once and for all at the beginning of the horizon while decision on the exact lot sizes can be deferred until the setup time. This operating scheme is referred to as the static-dynamic uncertainty strategy in the literature. For a capacitated system with minimum lot size restrictions, it has been shown that a modified base stock policy is optimal under the static-dynamic uncertainty strategy. However, the optimal policy parameters require an exhaustive search for which the computational time grows exponentially in the number of periods in the planning horizon. In order to alleviate the computational burden for real-life size problems, we develop and test seven diff erent heuristics for computational effi ciency and solution quality. Our extensive numerical experiments show that optimality gaps below 1% can be attained in reasonable running times by using a combination of these heuristics.