跳到主要內容

臺灣博碩士論文加值系統

(54.83.119.159) 您好!臺灣時間:2022/01/17 08:18
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:侯文哲
研究生(外文):Wen-Zhe Hou
論文名稱:護理人員排班資訊系統之建立與探討
指導教授:蔡長鈞蔡長鈞引用關係
指導教授(外文):Chang-Chun Tsai
學位類別:碩士
校院名稱:國立成功大學
系所名稱:工業管理科學系碩博士班
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:73
中文關鍵詞:資訊系統遺傳演算法護理人員排班
外文關鍵詞:genetic algorithmsinformation systemnurse scheduling
相關次數:
  • 被引用被引用:24
  • 點閱點閱:3543
  • 評分評分:
  • 下載下載:932
  • 收藏至我的研究室書目清單書目收藏:8
在醫院的管理中,護理人員的人力資源管理一向是最重要的議題,因此,關於護理人員班表的管理就顯得非常重要。以往,班表的管理都是護理長以人工的方式進行調度,即是由護理人員自行排定上班時段及休假日期,再由管理者做最後的統整,雖然人員的自主性提高,但是由於班表的數據資料龐大,考慮的因素又多,因此非常的費時費力,沒有效率,再加上用人工的方式,很難做到公平公正,影響人員的工作效率。
關於以往對於護理人員排班問題的相關研究中,在演算法方面,所採用的方法多半是利用整數規劃或是禁忌搜尋法的週期式排班方式,也有利用遺傳演算法的研究,來尋求可行解或是最適解。
綜合種種的因素,本研究利用互動式的網頁技術,再配合遺傳演算法的架構,提出一整合的排班系統,以方便護理長或相關的排班人員處理排班問題;在系統的介面方面,做到人員在處理排班問題時就像上網一樣簡單,降低人員操作電腦的困難度,在演算法核心方面,考慮系統的通用性及遺傳演算法的優點後,採用遺傳演算法的核心架構,在處理的機制上,配合個案的特性,在符合醫院政策、人員偏好、政府法規等等限制的前提下,達到以下二個目標。
1. 公平性目標:解決人工排班因考慮不週或個人本身喜惡因素產生的不合理現象,並減少人員紛爭。
2. 自主性目標:給予人員表示自我班別意願的空間,儘量在制度與人性上做一溝通協調。
The manpower management of nursing staff is always the most important subject in hospital management. So, it appears important to manage the work schedule of nursing staff. Formerly, nurse manager arranges the whole work schedule by hand. That is for nursing staff to arrange their work shift and off days by themselves and for nurse manager to balance the unit’s policy with the personal need. Though it gives the staffs with more autonomy property, it is time costly and inefficient due to the huge work shift data and the plenty considerable factors. By the way, it is hard to achieve fairness with the arrangement done by hand.

In the past, correlated researches about nurse scheduling were used by integer programming model, tabu search, cyclical scheduling as well as genetic algorithms, to generate feasible or suitable solution.

To synthesize, In order to simplify the multifarious details about nurse scheduling, this study brings up an integrated scheduling system bases on interactive web page technology and genetic algorithms. In system user interface, it will be as easy as browsing WWW to arrange the work schedule. In system algorithm core, it uses genetic algorithms as its optimal method. According to the restriction of hospital policies, staff preference and government rules, this study tries to achieve these two goals:
1. Fairness purpose: to solve the unfairness that is caused by carelessness or partiality of nurse manager.
2. Autonomy purpose: to coordinate between rules and humanity, that offers the staff a free chance to arrange their work shift and off days.
第一章 緒論 1
1.1研究動機 1
1.2研究對象 2
1.3研究目的 3
1.4研究限制 3
1.5研究流程 4
第二章 文獻探討 6
2.1勞動基準法 6
2.2排班 8
2.2.1 排班的定義 8
2.2.2 班表設計考量 9
2.2.3 護理人員排班的種類 10
2.3遺傳演算法 15
2.3.1 遺傳演算法之優點 15
2.3.2 遺傳演算法之步驟 16
2.4資訊系統程序與架構 22
第三章 個案問題模式與系統架構 27
3.1個案分析 27
3.1.1 個案問題描述 27
3.1.2 個案排班系統排班程序預擬 29
3.2系統架構及使用案例 31
3.3排班系統之數學模式 33
3.3.1 休假班表之排定 34
3.3.2 勤務班表之排定 35
第四章 系統介面與演算法則 38
4.1系統介面 38
4.2模式求解之演算法則探討 40
4.2.1 休假班表模式求解 40
4.2.1.1 休假班表之適合度函數 43
4.2.1.2 處理流程 43
4.2.2 勤務班表模式求解 46
4.2.2.1 勤務班表之適合度函數 47
4.2.2.2 處理流程 47
第五章 實證分析 51
5.1排班系統初始化設定 51
5.2系統之求解品質 54
5.3最佳解之判斷 56
5.3.1 自主性分析 56
5.3.2 公平性分析 57
第六章 結論與建議 58
6.1結論 58
6.2未來研究方向 59
[1]張斐章、陳莉(1993),「遺傳演算法於專家系統中參數優選之研究」,農業工程學報,第39卷第2期。
[2]陳建安(2000),「整合類神經網路與遺傳演算法為輔之模糊神經網路於智慧型訂單選取之應用」,國立台北科技大學生產系統工程與管理研究所碩士學位論文。
[3]莊凱翔(2001),「求解護理人員排班最佳化之研究-以遺傳演算法求解」,成功大學工業管理研究所碩士論文。
[4]Ahuja, H. and R. Sheppard (1975), “Computerized Nurse Scheduling,” Industrial Engineering, 7, pp. 24-29.
[5]Arther, J.L. and A. Ravindran (1981), “A Multiple Objective Nurse Scheduling Model,” AIIE Transaction, 13(1), pp. 56-60.
[6]Austin, S. (1990), “An Introduction to Genetic Algorithms,” AI Expert, pp.49-53.
[7]Bailey, J. (1985), “Integrated Days off and Shift Personnel Scheduling,” Computer and Operations Research, 9(4), pp. 395-402.
[8]Bell, P.C., G. Hay and Y. Liang (1986), “A Visual Interactive Decision Support System for Workforce(Nurse) Scheduling,” INFOR, 24(2), pp. 134-145.
[9]Brigitte, J., F. Semet and T. Vovor (1998), “A generalized linear programming model for nurse scheduling,” European Journal of Operational Research, 107, pp. 1-18.
[10]Dowsland, K.A. and J.M. Thompson (2000), “Solving a nurse scheduling problem with knapsacks, networks and tabu search,” Journal of the Operational Research Society, 51, pp. 825-833.
[11]Edwina, A.M. (2000), “Staffing and scheduling at your fingertips,” Nursing Management, 31(3), pp. 52-53.
[12]Felton, G. (1994), “Scheduling,” Nursing Management, pp. 258-268.
[13]Goldberg, D.E. (1989), “Genetic Algorithms in Search, Optimization, and Machine Learning,” Addison-Wesley.
[14]Grefenstette and J. John (1986), “Optimization of Control Parameters for Genetic Algorithms,” IEEE Trans. On Sys. Man, and Cyber., pp. 122-128.
[15]Harvey, H.M. and K. Mona (1998), “Cyclic and non-cyclic scheduling of 12 h shift nurses by network programming,” European Journal of Research, 104, pp. 582-592.
[16]Hung, R. (1991), “A cyclical Schedule of 10-hour, Four-day Workweeks,” Nursing Management, 22(9), pp. 30-33.
[17]Islier, A.A. (1998), “A Genetic Algorithm Approach for Multiple Criteria Facility Layout Design,” International Journal of Production Research, 36(6), pp. 1549-1569.
[18]Kostreva, M.M and K.S.B. Jenning (1991), “Nurse Scheduling on a Microcomputer,” Computers and Operations Research, 18(8), pp. 731-739.
[19]Kostreva, M.M., M.D. Lescyski and F.T. Passini (1978), “The nurse Scheduling decision via mixed-integer programming,” In Proceedings of American Hospital Association Forum on Nurse Scheduling, pp. 291-305.
[20]Lau, H.C. (1996), “On the Complexity of Manpower Shift Scheduling,” Computers Operations Research, 23(1), pp. 93-102.
[21]Marchionno, P.M. (1987), “Modified Cyclical Scheduling: A Practical Approach,” Nursing Management, 18(10).
[22]Miller, H.E., H.P. Pierskalla and G.J. Rsth (1976), “Nurse Scheduling Using Mathematical Programming,” Operations Research, 24(5), pp. 857-870.
[23]Musa, A.A. and U. Saxena (1984), “Scheduling Nurses using goal-programming techniques,” IIE Transactions, 16, pp. 216-221.
[24]Ozkarahan, I. and J.E. Bailey (1988), “Goal Programming Model Subsystem of a Flexible Nurse Scheduling Support System,” IIE Transactions, 20(3), pp. 306-316.
[25]Randhawa, S.U. and D. Stiompul (1993), “A Heuristic-Based Computerized Nurse Scheduling System,” Computers and Operations Research, 20(8), pp. 837-844.
[26]Rosenbloom, E.S. and N.F. Goertzen (1987), “Cyclic Nurse Scheduling,” European Journal of Operations Research, 31, pp. 19-23.
[27]Ruth, D., S.B. Dowd and K. Brownson (2000), “An equitable Nursing assignment structure,” Nursing Management, 31(2), pp. 33-34.
[28]Sharif, M. (2000), “Multireservious Systems Optimization Genetic Algorithms:Case Study,” Journal of Computing in Civil Engineering, 14(4).
[29]Smith, L.D. and A. Wiggins (1977), “A Computer-Based Nurse Scheduling System,” Computer and Operations Research, 4, pp. 195-212.
[30]Warner, D.M. and J. Prawda (1972), “A Mathematical Programming Model for Scheduling Nursing Personnel in a Hospital,” Management Science, 19(4), pp. 411-422.
[31]Warner, D.M. (1976), “Scheduling Nursing Personnel According to Nursing Preference: A Mathematical Programming Approach,” Operations Research, 24(5), pp. 842-856.
[32]Weil, G., etal. (1995), “Constraint Programming for Nurse Scheduling,” IEEE Engineering in Medicine and Biology, 14(4), pp. 417-422.
連結至畢業學校之論文網頁點我開啟連結
註: 此連結為研究生畢業學校所提供,不一定有電子全文可供下載,若連結有誤,請點選上方之〝勘誤回報〞功能,我們會盡快修正,謝謝!
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top