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Podcharapol Pongpatcharapun. Master surgical scheduling for multi-surgeon cases using a genetic algorithm. Master's Degree(Mathematics). Thammasat University. Thammasat University Library. : Thammasat University, 2020.
Master surgical scheduling for multi-surgeon cases using a genetic algorithm
keyword:
Master surgical scheduling
Abstract:
In this thesis, we propose a mixed-integer linear programming (MILP) model and a genetic algorithm (GA) to build a master surgical scheduling (MSS) for a case study of a large-sized Thai public hospital. Due to the large number of surgeries which must be handled each day, our main objective is to construct a schedule which maximizes the OR utilization, minimizes the room idle time between surgical cases, and minimizes the room overtime. The data from Tham- masat University Hospital were analyzed and simulated to generate a timetable from daily to weekly schedule. Our results show that an exact solution can be obtained by MILP for a simple problem while a large CPU run time is incurred for larger problems. GA provided the optimal solution for a complex large-scale problem after a chromosome elimination technique and the diversity rank were applied in the evolution process to overcome the local minima. We also simulated three different scenarios by varying the weights of idle time and overtime in the objective function. The first scenario is used when the surgery can be performed in working hours or overtime without considering the cost. The second scenario is used when the surgery can be scheduled during or after the working time with an room opening cost and overtime pay. The third scenario is used to arrange all surgeries with the maximum number of surgeries performed in the working hours. The performance of the proposed methods was compared to the actual schedule of the hospital. The results indicated that overtime and idle time are significantly improved in the schedule provided by proposed GA. Moreover, the schedule is more flexible and the staff can improve it to obtain more practical timetable in real situations, such as increasing the number of surgeries, setting a time block for specific surgical specialties, and handling emergency cases
Thammasat University. Thammasat University Library
Address:
BANGKOK
Email:
preserv@tu.ac.th
Name: Wanyok Atisattapong
Role:
advisor
Created:
2020
Modified:
2022-12-29
Issued:
2022-12-29
วิทยานิพนธ์/Thesis
application/pdf
eng
DegreeName: Master of Science
Level: Master's Degree
Descipline: Mathematics
Grantor: Thammasat University
©copyrights Thammasat University
RightsAccess:
ใช้เวลา
0.027191 วินาที
Podcharapol Pongpatcharapun
| Title | Contributor | Type |
|---|---|---|
| Master surgical scheduling for multi-surgeon cases using a genetic algorithm
มหาวิทยาลัยธรรมศาสตร์ Podcharapol Pongpatcharapun | Wanyok Atisattapong | วิทยานิพนธ์/Thesis |
Wanyok Atisattapong
| Title | Creator | Type and Date Create |
|---|---|---|
| Improved 1/t algorithm for approximating multidimentional numerical integration
มหาวิทยาลัยธรรมศาสตร์ Wanyok Atisattapong | Pasin Maruphanton | วิทยานิพนธ์/Thesis |
| Termination criteria of the Wang-Landau algorithm for multidimensional numerical integration
มหาวิทยาลัยธรรมศาสตร์ Wanyok Atisattapong | Jirarat Chairat | วิทยานิพนธ์/Thesis |
| Master surgical scheduling for multi-surgeon cases using a genetic algorithm
มหาวิทยาลัยธรรมศาสตร์ Wanyok Atisattapong | Podcharapol Pongpatcharapun | วิทยานิพนธ์/Thesis |
| Machine learning algorithms for predicting ESG scores : evidence from the Stock Exchange of Thailand
มหาวิทยาลัยธรรมศาสตร์ Wanyok Atisattapong | Chaiwat Promlum | วิทยานิพนธ์/Thesis |