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Related Concept Videos

Radiation Pressure: Problem Solving01:09

Radiation Pressure: Problem Solving

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The radiation pressure applied by an electromagnetic wave on a perfectly absorbing surface equals the energy density of the wave. The wave's momentum also gets transferred to the surface when an electromagnetic wave is entirely absorbed by it. The rate at which momentum is transmitted to an absorbing surface perpendicular to the propagation direction equals the force on the surface.
The average value of the rate of momentum transfer divided by the absorbing area represents the average force...
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Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
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A two-phase approach for the Radiotherapy Scheduling Problem.

Tu-San Pham1, Louis-Martin Rousseau2, Patrick De Causmaecker3

  • 1Polytechnique Montréal, Montréal, Canada. tu-san.pham@polymtl.ca.

Health Care Management Science
|September 10, 2021
PubMed
Summary
This summary is machine-generated.

This study optimizes radiotherapy scheduling for cancer patients using a two-phase approach. Constraint Programming (CP) efficiently finds solutions, while batch scheduling reduces patient wait times.

Keywords:
Constraint ProgrammingInteger ProgrammingOperations researchRadiotherapy schedulingSimulation

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Area of Science:

  • Operations Research
  • Medical Informatics
  • Cancer Treatment

Background:

  • Radiotherapy treatment planning involves complex scheduling challenges.
  • Optimizing radiotherapy scheduling is crucial for patient care and resource utilization.

Purpose of the Study:

  • To develop and evaluate a two-phase approach for the Radiotherapy Scheduling Problem (RTSP).
  • To compare Integer Linear Programming (IP), Mixed Integer Linear Programming (MIP), and Constraint Programming (CP) for RTSP.

Main Methods:

  • A two-phase optimization strategy was implemented for RTSP.
  • Phase 1: Session assignment to linear accelerators (linacs) and days using IP.
  • Phase 2: Patient sequencing and appointment timing using MIP and CP.

Main Results:

  • CP models demonstrated faster solution generation in phase 2.
  • MIP models were more effective in reducing optimality gaps with extended computation time.
  • Simulation indicated batch scheduling significantly reduces patient waiting and overdue times.

Conclusions:

  • The proposed two-phase approach effectively addresses the RTSP.
  • CP offers a practical advantage for rapid scheduling, while MIP aids in refining solutions.
  • Batch scheduling is a promising strategy for improving radiotherapy workflow efficiency.