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Tabu search with fully sequential procedure for simulation optimization

Authors: Çevik, Savaş;

Tabu search with fully sequential procedure for simulation optimization

Abstract

ÖZET SİMÜLAS YONLA ENİYİLEME İÇİN TABU ARAMASI İLE BİRLEŞTİRİLMİŞ SIRALI SEÇİM METODU Savaş Çevik Endüstri Mühendisliği, Yüksek Lisans Tez Yöneticisi: Prof. Dr. İhsan Sabuncuoğlu Ağustos 2003 Simülasyon var olan veya tasarım aşamasındaki sistemlerin davranışlarını anlamak için kullanılan tanımlayıcı bir araçtır. Var olan sistemlerin çoğu dinamik ve rassal bir yapıya sahiptir. Bu durum sistemin analitik bir modelini çıkarmayı güçleştirebilir. Simülasyon bu tür sistemlerin modellenmesinde ve analiz edilmesinde kullanılabilir. Sistem davranışı hakkında çok yararlı bilgiler sağlasa da, simülasyon tek başına sistem performansını eniyilemede kullanılamaz. Son yıllarda, sezgisel yöntemlerin geliştirilmesiyle birlikte, simülasyonla eniyileme kavramı büyük önem kazanmıştır. Simülasyonla eniyileme teknikleri simülasyonu bir değerleme aracı olarak kullanır ve simülasyon girdi değerlerini uygun şekilde ayarlayarak sistemin performansını en iyilemeye çalışır. Diğer taraftan, istatiksel sıralama ve seçim metodlan belirli bir güven seviyesiyle alternatif sistemler içinden en iyi sistemi seçmek için kullanılırlar. Bu çalışmada, bu iki metodolojiyi birleştirdik ve ortaya çıkan hibrid metodun performansını inceledik. Tabu Araması, Tamamen Sıralı Seçim metoduyla simülasyonla eniyileme bağlamında birleştirildi. Ortaya çıkan metodun performansı dört farklı sistem üzerinde denendi. Tamamen Sıralı Seçim metodunun etkinliği hesapsal efor ve en iyi çözüme yakınsama göz önünde tutularak değerlendirildi. Anahtar kelimeler: Simülasyonla eniyileme, sıralama ve seçim metodlan, tabu araması, tamamen sıralı seçim metodu.

ABSTRACT TABU SEARCH WITH FULLY SEQUENTIAL PROCEDURE FOR SIMULATION OPTIMIZATION Savaş Çevik M.S. in Industrial Engineering Advisor: Prof. İhsan Sabımcuoğlu August,2003 Simulation is a descriptive technique that is used to understand the behaviour of both conceptual and real systems. Most of the real life systems are dynamic and stochastic that it may be very difficult to derive analytical representation. Simulation can be used to model and to analyze these systems. Although simulation provides insightful information about the system behaviour, it cannot be used to optimize the system performance. With the development of the metaheuristics, the concept simulation optimization has became a reality in recent years. A simulation optimization technique uses simulation as an evaluator, and tries to optimize the systems performance by setting appropriate values of simulation input. On the other hand, statistical ranking and selection procedures are used to find the best system design among a set of alternatives with a desired confidence level. In this study, we combine these two methodologies and investigate the performance of the hybrid procedure. Tabu Search (TS) heuristic is combined with the Fully Sequential Procedure (FSP) in simulation optimization context. The performance of the combined procedure is examined in four different systems. The effectiveness of the FSP is assessed considering the computational effort and the convergence to the best (near optimal) solution. Keywords: Simulation Optimization, Ranking and Selection, Tabu Search, Fully Sequential Procedure.

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Turkey
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Keywords

Mathematical optimization., QA402.S95 C48 2003, Mathematical optimization, Endüstri ve Endüstri Mühendisliği, Tabu Search, Fully Sequential Procedure, 006, Ranking and Selection, Simulation Optimization, Industrial and Industrial Engineering

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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