Genetic Algorithm Based Scheduling of Radiotherapy Treatments for Cancer Patients

Dobrila Petrovic; Mohammad Morshed; Sanj Petrovic

doi:10.1007/978-3-642-02976-9_14

Genetic Algorithm Based Scheduling of Radiotherapy Treatments for Cancer Patients

Dobrila Petrovic, Mohammad Morshed, Sanj Petrovic

Research output: Contribution to journal › Article

16 Citations (Scopus)

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	https://doi.org/10.1007/978-3-642-02976-9_14
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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-642-02976-9_14

Cite this

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title = "Genetic Algorithm Based Scheduling of Radiotherapy Treatments for Cancer Patients",

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.",

keywords = "Radiotherapy, Genetic Algorithms, Scheduling, Waiting Times",

author = "Dobrila Petrovic and Mohammad Morshed and Sanj Petrovic",

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.",

year = "2009",

doi = "10.1007/978-3-642-02976-9_14",

language = "English",

volume = "5651",

pages = "101--105",

journal = "Lecture Notes in Computer Science",

issn = "0302-9743",

publisher = "Springer Verlag",

number = "2009",

}

TY - JOUR

T1 - Genetic Algorithm Based Scheduling of Radiotherapy Treatments for Cancer Patients

AU - Petrovic, Dobrila

AU - Morshed, Mohammad

AU - Petrovic, Sanj

N1 - 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.

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

KW - Radiotherapy

KW - Genetic Algorithms

KW - Scheduling

KW - Waiting Times

U2 - 10.1007/978-3-642-02976-9_14

DO - 10.1007/978-3-642-02976-9_14

M3 - Article

VL - 5651

SP - 101

EP - 105

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

IS - 2009

ER -

Genetic Algorithm Based Scheduling of Radiotherapy Treatments for Cancer Patients

Abstract

Bibliographical note

Keywords

UN SDGs

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