Global Best Harmony Search With A New Pitch Adjustment Designed For Nurse Rostering
| المصدر: | مجلة جامعة الملك سعود - علوم الحاسب والمعلومات |
|---|---|
| الناشر: | جامعة الملك سعود |
| المؤلف الرئيسي: | Awadallah, Mohammed A. (Author) |
| مؤلفين آخرين: | Khader, Ahamad Tajudin (Co-Author) , Al-Betar, Mohammed Azmi (Co-Author) , Bolaji, Asaju La’aro (Co-Author) |
| المجلد/العدد: | مج25, ع2 |
| محكمة: | نعم |
| الدولة: |
السعودية |
| التاريخ الميلادي: |
2013
|
| الصفحات: | 145 - 162 |
| DOI: |
10.33948/0584-025-002-004 |
| ISSN: |
1319-1578 |
| رقم MD: | 972925 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | science |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Nurse Rostering | Harmony Search | Approximation Method | Population Based | Global Best
|
| رابط المحتوى: |
| المستخلص: |
In this paper, the Harmony Search Algorithm (HSA) is proposed to tackle the Nurse Rostering Problem (NRP) using a dataset introduced in the First International Nurse Rostering Competition (INRC2010). NRP is a combinatorial optimization problem that is tackled by assigning a set of nurses with different skills and contracts to different types of shifts, over a predefined scheduling period. HSA is an approximation method which mimics the improvisation process that has been successfully applied for a wide range of optimization problems. It improvises the new harmony iteratively using three operators: memory consideration, random consideration, and pitch adjustment. Recently, HSA has been used for NRP, with promising results. This paper has made two major improvements to HSA for NRP: (i) replacing random selection with the Global-best selection of Particle Swarm Optimization in memory consideration operator to improve convergence speed. (ii) Establishing multi-pitch adjustment procedures to improve local exploitation. The result obtained by HSA is comparable with those produced by the five INRC 2010 winners’ methods. |
|---|---|
| ISSN: |
1319-1578 |
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