應用改良式變動鄰近搜尋法求解醫院急診室醫師排班最佳化問題

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研究生：	胡利歐 Sanchez Avellan, Julio-Eduardo
論文名稱：	應用改良式變動鄰近搜尋法求解醫院急診室醫師排班最佳化問題 Modified Variable Neighborhood Search Algorithm for Physician Rostering Optimization Problem in a Hospital Emergency Department
指導教授：	陳建良 Chen, James-C.
口試委員:	洪一峯 Hung, Yi-Feng 陳子立 Chen, Tzu-Li
學位類別：	碩士 Master
系所名稱：	工學院 - 工業工程與工程管理學系 Department of Industrial Engineering and Engineering Management
論文出版年：	2019
畢業學年度：	107
語文別：	英文
論文頁數：	90
中文關鍵詞：	改良式變動鄰近搜尋法、醫師排班最佳化問題
外文關鍵詞：	Variable Neighborhood Search, Physician Rostering Optimization
相關次數：	點閱：2 下載：0
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Physician Rostering Optimization（PRO）問題被定義為在指定的計劃範圍內，考慮到某些規則，規則或約束，將許多醫生分配到不同的班次。在現實生活中解決這個問題通常非常具有挑戰性，特別是採用獨特的方法在這項研究中，提出了一種改進的變鄰域搜索（VNS）算法來開發一種求解PRO問題的方法。當前方法由兩個階段組成，I階段通過使用貪婪啟發式方法開發初始解決方案，該方法滿足問題的所有硬約束，此後方法的II階段開始，旨在改進採用可變鄰域下降（VND）算法的初始解決方案。然後，在VNS算法中固定的振動階段增強所生成的解決方案，以便檢查是否可以獲得更好的解決方案。為了確定當前解決方案的質量，當前的研究使用目標函數的可變性，可變性是由於未完全實現軟約束而產生的懲罰。基於實驗設計（DOE）確定適當的算法設置，25個實例的計算結果獲得了更好的結果，所提出的算法在大多數情況下都優於經典VNS和兩個修改現行方法。

The Physician Rostering Optimization (PRO) problem is defined as the assignation of a number of physicians to different shifts during a specified planning horizon, considering certain rules, regulations or constraints. This is often very challenging to solve in real life especially applying a unique approach. In this research, a Modified Variable Neighborhood Search (VNS) algorithm is proposed to develop a method to solver the PRO problem. the current method is composed by in two phases, the I phase to develop an initial solution through the use of a greedy heuristic method which meets all the hard constraints of the problem, after this the II phase of the method starts which aims to improve the initial solution employing a Variable Neighborhood Descent (VND) algorithm. Then the Shaking phase, which is fixed in the VNS algorithm boost the generated solution in order to check whether or not, is possible to obtain a better one. To determine the quality of the current solution the current research use the variability of the objective function, the variability is the penalty generated due to the not full achievement of the soft constraints. Based on the Design of Experiments (DOE) to determine the appropriate algorithm setting the computational result of 25 instances were obtained a better result with the proposed algorithm which outperforms in most of the instances when it was compared with a classic VNS and two modifications of the current method.

Contents
Abstract    II
摘要    III
Acknowledgments    IV
Contents    V
List of Tables    VII
List of Figures    VII
Chapter 1    Introduction    8
1.1    Background and Motivation    8
1.2    Research Objective    9
1.3    Research Method    9
Chapter 2    Literature Review    10
2.1    Health Care Rostering Problem    10
2.2    Variable Neighborhood Search    19
2.3    Integer Programming Approach    20
Chapter 3    Problem Definition    21
3.1    Problem Statement    21
3.2    Mathematical Model    21
Chapter 4    Methodology    25
4.1    I Stage: Initial Solution    27
4.2    II Stage: VNS Algorithm    30
Chapter 5    Experiments and Results    36
5.1    Dataset information    37
5.2    Parameter settings determination    38
5.3    Generation of instances    43
5.4    Analysis of different types of VNS algorithms    45
Chapter 6    Conclusion    55
References    58
Appendices    60
Appendix A: Manual verification of hard constraints    60
Appendix B: Design of Experiments (DOE) sample of replicates results    62
Appendix C: Sample of Instances schedules results    69
Appendix D: Replicates for the 25 instances (3 replicates per instance)    87


                                

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