Ameliyat odası çizelgelemenin genetik algoritma ile gerçekleştirilmesi
Yükleniyor...
Dosyalar
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Düzce Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Bu tezde, hastanelerin en önemli birimlerinden birisi olan Ameliyat Odalarının en verimli şekilde kullanılabilmesi problemi ele alınmıştır. Bu problem tipi NP-Hard tipi problem olarak adlandırılmaktadır. NP-Hard tipi problem tanım olarak, çok sayıda kısıt içeren karmaşık problemler için kullanılmaktadır. NP-Hard tipi problemin, polinom değerlerden oluşmaması çözümünü karmaşıklaştırmaktadır. Bu tip problemlerin çözümü geleneksel matematiğe dayalı yöntemlerle olmamakta ve sayısal analiz yöntemleri kullanılarak ise sağlıklı sonuçlar elde edilememektedir. Karmaşıklık seviyesi fazla olan ve çok sayıda kısıt içeren NP-Hard tipi problemlerin çözümü için Genetik Algoritma (GA), tabu arama, benzetimli tavlama gibi sezgisel ve meta-sezgisel algoritmalar ortaya çıkmıştır. Ameliyat odası çizelgeleme problemi ise bu tezde en önemli meta-sezgisel algoritmalardan birisi olan genetik algoritma ile çözülmüştür. Program kodlanırken görselliği de sağlamak amacıyla C# programlama dili tercih edilmiştir. Ayrıca tamir operatörünün bu tip problemlerde genetik algoritmanın bir operatörü olarak kullanılmasının etkisi ve önemi de incelenmiştir.
In this thesis, the problem of the most efficient use of the Operating Rooms (ORs) which one of the most important departments of hospitals, was tackled. This type of problem is defined as NP-Hard. Complex problems involving multiple constraints are defined as NP-Hard type problems. As the NP-Hard type problem does not consist of polynomial values, the solution of such problems becomes complicated. Such problems cannot be solved by traditional methods based on mathematics. In addition, healthy results cannot be obtained by using numerical analysis methods. For the solution of NP-Hard type problems which have high level of complexity and many constraints, heuristic and meta-heuristic algorithms such as Genetic Algorithm (GA), tabu search, simulated annealing have emerged. In this thesis, the operating room scheduling problem is solved by the genetic algorithm, which is one of the most important meta-heuristic algorithms. C# programming language is preferred to provide visuality when coding the program. Furthermore, the effect and the importance of using the repair operator as an operator of the genetic algorithm in these types of problems were also investigated.
In this thesis, the problem of the most efficient use of the Operating Rooms (ORs) which one of the most important departments of hospitals, was tackled. This type of problem is defined as NP-Hard. Complex problems involving multiple constraints are defined as NP-Hard type problems. As the NP-Hard type problem does not consist of polynomial values, the solution of such problems becomes complicated. Such problems cannot be solved by traditional methods based on mathematics. In addition, healthy results cannot be obtained by using numerical analysis methods. For the solution of NP-Hard type problems which have high level of complexity and many constraints, heuristic and meta-heuristic algorithms such as Genetic Algorithm (GA), tabu search, simulated annealing have emerged. In this thesis, the operating room scheduling problem is solved by the genetic algorithm, which is one of the most important meta-heuristic algorithms. C# programming language is preferred to provide visuality when coding the program. Furthermore, the effect and the importance of using the repair operator as an operator of the genetic algorithm in these types of problems were also investigated.
Açıklama
YÖK Tez No: 542808
Anahtar Kelimeler
Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol, Computer Engineering and Computer Science and Control, Genetik algoritmalar, Genetic algorithms, Zaman çizelgeleme, Timetabling, Çok kriterli optimizasyon, Multi criteria optimization
