Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service
In this paper, we study a complex outpatient planning problem in the chemotherapy department. The planning concerns sequences of patients’ treatment sessions subject to exact in-between resting periods (i.e., exact time-lags). The planning is constrained by the hospital infrastructure and the availa...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/2/659 |
| _version_ | 1797496137693790208 |
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| author | Quoc Nhat Han Tran Nhan Quy Nguyen Hicham Chehade Lionel Amodeo Farouk Yalaoui |
| author_facet | Quoc Nhat Han Tran Nhan Quy Nguyen Hicham Chehade Lionel Amodeo Farouk Yalaoui |
| author_sort | Quoc Nhat Han Tran |
| collection | DOAJ |
| description | In this paper, we study a complex outpatient planning problem in the chemotherapy department. The planning concerns sequences of patients’ treatment sessions subject to exact in-between resting periods (i.e., exact time-lags). The planning is constrained by the hospital infrastructure and the availability of medical staff (i.e., multiple time-varying resources’ availability). In order to maximize the patients’ service quality, the objective of the function considered is to minimize the total wait times, which is equivalent to the criteria for minimizing the total completion time. Our main contribution is a thorough analysis of this problem, using the Hybrid Flow Shop problem as a theoretical framework to study the problem. A novel Mixed Integer Linear Programming (MILP) is introduced. Concerning the resolution methods, priority-based heuristics and an adapted genetic algorithm (GA) are presented. Numerical experiments are conducted on historical data to compare the performances of the approximate resolution methods against the MILP solved by CPLEX. Numerical results confirm the performances of the proposed methods. |
| first_indexed | 2024-03-10T01:59:22Z |
| format | Article |
| id | doaj.art-f8a4b09a07684089ad9d9e45500cb6c6 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T01:59:22Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-f8a4b09a07684089ad9d9e45500cb6c62023-11-23T12:50:39ZengMDPI AGApplied Sciences2076-34172022-01-0112265910.3390/app12020659Outpatient Appointment Optimization: A Case Study of a Chemotherapy ServiceQuoc Nhat Han Tran0Nhan Quy Nguyen 1Hicham Chehade2Lionel Amodeo3Farouk Yalaoui4Opta LP S.A.S., 2 Rue Gustave Eiffel, 10430 Rosieres-pres-Troyes, FranceComputer Sciences and Digital Society Laboratory (LIST3N), Université de Technologie de Troyes, 12 Rue Marie Curie, CS 42060, 10004 Troyes, FranceOpta LP S.A.S., 2 Rue Gustave Eiffel, 10430 Rosieres-pres-Troyes, FranceComputer Sciences and Digital Society Laboratory (LIST3N), Université de Technologie de Troyes, 12 Rue Marie Curie, CS 42060, 10004 Troyes, FranceComputer Sciences and Digital Society Laboratory (LIST3N), Université de Technologie de Troyes, 12 Rue Marie Curie, CS 42060, 10004 Troyes, FranceIn this paper, we study a complex outpatient planning problem in the chemotherapy department. The planning concerns sequences of patients’ treatment sessions subject to exact in-between resting periods (i.e., exact time-lags). The planning is constrained by the hospital infrastructure and the availability of medical staff (i.e., multiple time-varying resources’ availability). In order to maximize the patients’ service quality, the objective of the function considered is to minimize the total wait times, which is equivalent to the criteria for minimizing the total completion time. Our main contribution is a thorough analysis of this problem, using the Hybrid Flow Shop problem as a theoretical framework to study the problem. A novel Mixed Integer Linear Programming (MILP) is introduced. Concerning the resolution methods, priority-based heuristics and an adapted genetic algorithm (GA) are presented. Numerical experiments are conducted on historical data to compare the performances of the approximate resolution methods against the MILP solved by CPLEX. Numerical results confirm the performances of the proposed methods.https://www.mdpi.com/2076-3417/12/2/659outpatientplanning techniqueshybrid flow shoptime-lagtime-varying resourcesgenetic algorithm |
| spellingShingle | Quoc Nhat Han Tran Nhan Quy Nguyen Hicham Chehade Lionel Amodeo Farouk Yalaoui Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service Applied Sciences outpatient planning techniques hybrid flow shop time-lag time-varying resources genetic algorithm |
| title | Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service |
| title_full | Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service |
| title_fullStr | Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service |
| title_full_unstemmed | Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service |
| title_short | Outpatient Appointment Optimization: A Case Study of a Chemotherapy Service |
| title_sort | outpatient appointment optimization a case study of a chemotherapy service |
| topic | outpatient planning techniques hybrid flow shop time-lag time-varying resources genetic algorithm |
| url | https://www.mdpi.com/2076-3417/12/2/659 |
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