Sampling based progressive hedging algorithms for stochastic programming problems
Başlık çevirisi mevcut değil.
- Tez No: 400016
- Danışmanlar: Belirtilmemiş.
- Tez Türü: Doktora
- Konular: Endüstri ve Endüstri Mühendisliği, Industrial and Industrial Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2012
- Dil: İngilizce
- Üniversite: Wayne State Unıversıty
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: Belirtilmemiş.
Özet
Özet yok.
Özet (Çeviri)
Many real-world optimization problems have parameter uncertainty. Forinstances where the uncertainties can be estimated to a certain degree, stochasticprogramming (SP) methodologies are used to identify robust plans. Despiteadvances in SP, it is still a challenge to solve real world stochastic programmingproblems, in part due to the exponentially increasing number of scenarios. For twostageand multi-stage problems, the number of scenarios increases exponentiallywith the number of uncertain parameters, and for multi-stage problems also with thenumber of decision stages.In the case of large scale mixed integer stochastic problem instances, thereare usually two common approaches: approximation methods and decompositionmethods. Most common sampling-based approximation (SAA) SP technique is theMonte Carlo sampling-based method. The Progressive Hedging Algorithm (PHA) onthe other hand can optimally solve large problems through the decomposition intosmaller problem instances. The SAA, while effectively used in many applications, canlead to poor solution quality if the selected sample sizes are not sufficiently large.With larger sample sizes and multi-stage SPs, however, the SAA method is notpractical due to the significant computational effort required. In contrast, PHA suffersfrom the need to solve many sub-problems iteratively which is computationallyexpensive.In this dissertation, we develop novel SP algorithms integrating samplingbased SAA and decomposition based PHA SP methods. The proposed integratedmethods are novel in that they marry the complementary aspects of PHA and SAA interms of exactness and computational efficiency. Further, the developed methods arepractical in that they allow the analyst to calibrate the tradeoff between the exactnessand speed of attaining a solution.We demonstrate the effectiveness of the developed integrated approaches,Sampling Based Progressive Hedging Algorithm (SBPHA) and Discarding SBPHA (d-SBPHA), over the pure strategies (i.e. SAA or PHA) as well as other commonly usedSP methods through extensive experimentation. In addition, we develop alternativehybridization strategies and present results of extensive experiments for thesestrategies under different uncertainty models. The validation of the methods isdemonstrated through Capacitated Reliable facility Location Problem (CRFLP) andMulti-stage stochastic lot-sizing problems.
Benzer Tezler
- Modelıng dısease progressıon wıth dıffusıon-based generatıve models
Difüzyon tabanlı üretken modellerle hastalık ilerleyişinin modellenmesi
MERYEM MİNE KURT
Yüksek Lisans
İngilizce
2025
Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve KontrolOrta Doğu Teknik ÜniversitesiModelleme ve Simülasyon Ana Bilim Dalı
PROF. DR. ALPTEKİN TEMİZEL
- Accelerated MRI sampling and reconstruction with reinforcement learning
Pekiştirmeli öğrenme ile hızlandırılmış MRG örnekleme ve geriçatımı
RURU XU
Doktora
İngilizce
2026
Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrolİstanbul Teknik ÜniversitesiBilgisayar Mühendisliği Ana Bilim Dalı
Assoc. Prof. Dr. İLKAY ÖKSÜZ
- Design of a wearable sensor system for artificial intelligence based motion analysis in telerehabilitation
Telerehabilitasyon amaçlı yapay zekâ tabanlı hareket analizi içingiyilebilir sensör sistemi tasarımı
AHMED ABDELWAHAB MAHGOUB HAKIM
Yüksek Lisans
İngilizce
2025
Elektrik ve Elektronik MühendisliğiHacettepe ÜniversitesiElektrik-Elektronik Mühendisliği Ana Bilim Dalı
DOÇ. DR. ŞÖLEN KUMBAY YILDIZ
PROF. DR. ATİLA YILMAZ
- Frekans seçici yüzeyler (FSY) ile duyarlılığı iyileştirilmiş mikroşerit yama antenli hibrit yakın alan glikoz tespit sensörü tasarımı
Design of a hybrid near-field glucose sensing sensor based on a microstrip patch antenna with sensitivity enhancement using frequency selective surfaces (FSS)
UMUT KÖSE
Doktora
Türkçe
2026
Elektrik ve Elektronik Mühendisliğiİstanbul Teknik ÜniversitesiElektronik ve Haberleşme Mühendisliği Ana Bilim Dalı
PROF. DR. MESUT KARTAL
- Gerçek zamanlı bir hücresel sinir ağı yapısının tasarımı ve bu yapıyla Gabor filtrelerinin FPGA üzerinde gerçeklenmesi
Design of a real-time cellular neural network structure and its implementation on an FPGA device for the realization of Gabor filters
EVREN CESUR
Doktora
Türkçe
2013
Elektrik ve Elektronik MühendisliğiYıldız Teknik ÜniversitesiElektronik ve Haberleşme Mühendisliği Ana Bilim Dalı
PROF. DR. VEDAT TAVŞANOĞLU