Abstract
This paper presents a multi-objective model for scheduling of radiotherapy treatments for cancer patients based on genetic algorithms (GA). The model is developed and implemented considering real life radiotherapy treatment processes at Arden Cancer Centre, Coventry, UK. Two objectives are defined: minimisation of the Average patient waiting times and minimisation of Average tardiness of the patient first treatment fractions. Two scenarios are analysed considering the availability of the doctors to approve treatment plans. The schedules generated by the GA using real data collected from the collaborating Cancer Centre have good performance. It is demonstrated that enabling doctors to approve treatment plans instantly has a great impact on Average waiting time and Average tardiness for all patient categories.
Original language | English |
---|---|
Pages (from-to) | 101-105 |
Journal | Lecture Notes in Computer Science |
Volume | 5651 |
Issue number | 2009 |
DOIs | |
Publication status | Published - 2009 |
Bibliographical note
This paper is not available on the repository. The paper was given at the 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Verona, Italy, July 18-22, 2009.Keywords
- Radiotherapy
- Genetic Algorithms
- Scheduling
- Waiting Times