Genetic algorithm based on weighted goal programming for doctor rostering problem

Anıl Yalçın; Derya Deliktaş

Makale detayları

Genetic algorithm based on weighted goal programming for doctor rostering problem

Yazarlar:

Anıl Yalçın | Derya Deliktaş

Yayıncı:

Gazi University

Ana Başlıklar:

Memnuniyet ve Optimizasyon | Endüstri Mühendisliği

Dergi:

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi Vol.39 Issue 4, pp.2567-2586

Belge Tipi:

Makale

Yayın Tarihi:

5/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001317571

pISSN:

1300-1884

Anahtar kelimeler:

Özet:

 In the healthcare sector, undisrupted service is essential for hospitals. Therefore, shift work plays a vital role in satisfying constraints such as coverage requirements and government regulations. The doctor rostering problem is classified as an NP-hard problem due to its complexity and scale. In addition to the fairness of assignments, including hospital management policies, and government regulations, many related factors must be taken into account during the scheduling process in this scheduling problem. This study aims to generate a rostering system that can satisfy the requirements of the hospital, ensure fairness amongst the doctors, and take preferences into account. A genetic algorithm based on a weighted goal programming model was proposed to solve the doctor rostering problem. The proposed model was applied to the Internal Diseases Department and the Lateral Branches Department of Kütahya Evliya Çelebi Education and Research Hospital. 15 different scenarios were constructed, considering different problem scales and different preference patterns of the doctors that may occur in the the future. It is approved that the proposed algorithm can be applied to different problem scales and conditions. The parameters of the proposed algorithm were calibrated with an experimental design method. In this study, two main contributions were presented. A model with new constraints was introduced for researchers. In addition, a genetic algorithm based on weighted goal programming was proposed to solve the problem and applied to a real-world case study.

 In the healthcare sector, undisrupted service is essential for hospitals. Therefore, shift work plays a vital role in satisfying constraints such as coverage requirements and government regulations. The doctor rostering problem is classified as an NP-hard problem due to its complexity and scale. In addition to the fairness of assignments, including hospital management policies, and government regulations, many related factors must be taken into account during the scheduling process in this scheduling problem. This study aims to generate a rostering system that can satisfy the requirements of the hospital, ensure fairness amongst the doctors, and take preferences into account. A genetic algorithm based on a weighted goal programming model was proposed to solve the doctor rostering problem. The proposed model was applied to the Internal Diseases Department and the Lateral Branches Department of Kütahya Evliya Çelebi Education and Research Hospital. 15 different scenarios were constructed, considering different problem scales and different preference patterns of the doctors that may occur in the the future. It is approved that the proposed algorithm can be applied to different problem scales and conditions. The parameters of the proposed algorithm were calibrated with an experimental design method. In this study, two main contributions were presented. A model with new constraints was introduced for researchers. In addition, a genetic algorithm based on weighted goal programming was proposed to solve the problem and applied to a real-world case study.

 In the healthcare sector, undisrupted service is essential for hospitals. Therefore, shift work plays a vital role in satisfying constraints such as coverage requirements and government regulations. The doctor rostering problem is classified as an NP-hard problem due to its complexity and scale. In addition to the fairness of assignments, including hospital management policies, and government regulations, many related factors must be taken into account during the scheduling process in this scheduling problem. This study aims to generate a rostering system that can satisfy the requirements of the hospital, ensure fairness amongst the doctors, and take preferences into account. A genetic algorithm based on a weighted goal programming model was proposed to solve the doctor rostering problem. The proposed model was applied to the Internal Diseases Department and the Lateral Branches Department of Kütahya Evliya Çelebi Education and Research Hospital. 15 different scenarios were constructed, considering different problem scales and different preference patterns of the doctors that may occur in the the future. It is approved that the proposed algorithm can be applied to different problem scales and conditions. The parameters of the proposed algorithm were calibrated with an experimental design method. In this study, two main contributions were presented. A model with new constraints was introduced for researchers. In addition, a genetic algorithm based on weighted goal programming was proposed to solve the problem and applied to a real-world case study.

 Sağlık hizmeti alanında, hastaneler için kesintisiz hizmet esastır. Bu nedenle, vardiyalı çalışma, talep kısıtları ve devlet düzenlemeleri gibi kısıtların karşılanabilmesi açısından oldukça önemli bir rol oynamaktadır. Doktor nöbet cetveli çizelgeleme problemi, problemin karmaşıklığı ve büyüklüğü sebebiyle NP-zor problem grubu içerisinde tanımlanmaktadır. Bu çizelgeleme probleminde, atamaların adilliğine ek olarak, hastane yönetim politikaları ve hükümet düzenlemeleri dâhil olmak üzere ilgili pek çok faktör hesaba katılmalıdır. Bu çalışma, hastane gereksinimlerini, doktorlar arasındaki adilliği karşılayabilen ve doktor tercihlerini göz önünde bulundurabilen bir nöbet cetveli çizelgeleme sistemi oluşturmayı amaçlamıştır. Ele alınan nöbet cetveli çizelgeleme probleminin çözümü için bir ağırlıklı hedef programlama-tabanlı genetik algoritma önerilmiştir. Önerilen model Kütahya Evliya Çelebi Eğitim ve Araştırma Hastanesi Dahiliye Departmanı ve İç Hastalıkları Departmanına uygulanmıştır. Gelecekte, oluşabilecek problem boyutları, şartları ve farklı tercih modelleri düşünülerek 15 farklı senaryo oluşturulmuştur. Bu senaryolarla önerilen algoritmanın farklı durumlarda da uygulanabilir olduğu gösterilmiştir. Önerilen algoritmanın parametreleri, bir deneysel tasarım yöntemiyle kalibre edilmiştir. Bu çalışma ile iki ana katkıda bulunulmuştur. Araştırmacılar için yeni kısıtlara sahip bir model önerilmiştir. Ek olarak, problemin çözümü için bir ağırlıklı hedef programlama-tabanlı genetik algoritma önerilerek gerçek-hayat problemine uygulanmıştır.

Makale detayları

Genetic algorithm based on weighted goal programming for doctor rostering problem

Yazarlar:

Anıl Yalçın | Derya Deliktaş

Yayıncı:

Gazi University

Ana Başlıklar:

Memnuniyet ve Optimizasyon | Endüstri Mühendisliği

Dergi:

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi Vol.39 Issue 4, pp.2567-2586

Belge Tipi:

Makale

Yayın Tarihi:

5/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001317571

pISSN:

1300-1884

Doctor rostering

experimental design

genetic algorithm

weighted goal programming

sensitivity analysisAğırlıklı hedef programlama

deney tasarımı

doktor nöbet cetveli çizelgeleme

genetik algoritma

duyarlılık analizi

Sayı

Makale detayları

Yazarlar: Anıl Yalçın | Derya Deliktaş

Yayıncı: Gazi University

Ana Başlıklar: Memnuniyet ve Optimizasyon | Endüstri Mühendisliği

Dergi: Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi Vol.39 Issue 4, pp.2567-2586

Belge Tipi: Makale

Yayın Tarihi: 5/2024

Belge Dili: Türkçe

Document ID (Org No.): 2001317571

pISSN: 1300-1884

Sayı

Yazarlar:

Anıl Yalçın | Derya Deliktaş

Yayıncı:

Gazi University

Ana Başlıklar:

Memnuniyet ve Optimizasyon | Endüstri Mühendisliği

Dergi:

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi Vol.39 Issue 4, pp.2567-2586

Belge Tipi:

Makale

Yayın Tarihi:

5/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001317571

pISSN:

1300-1884