Decomposition techniques with mixed integer programming and heuristics for home healthcare planning

Area of Science:

• Operations Research
• Healthcare Management
• Computer Science

Background:

• Home healthcare planning integrates complex scheduling and routing challenges.
• Real-world instances of these problems are computationally demanding for existing optimization solvers.

Purpose of the Study:

• To develop and evaluate decomposition methods for UK home healthcare planning.
• To enhance the practical application of mixed integer programming and heuristics for these problems.

Main Methods:

• Decomposition of the planning problem into smaller sub-problems.
• Application of mixed integer programming and/or heuristics to solve sub-problems.
• Integration of sub-problem solutions into a unified, valid plan.

Main Results:

• Proposed decomposition methods yield high-quality solutions for real-world home healthcare planning instances.
• The study analyzes the contribution of individual method components to overall performance.
• Comparison with other methods demonstrates the effectiveness of the proposed approach.

Conclusions:

• Effective combination of mixed integer programming within decomposition methods is crucial.
• The research provides practical computation time solutions for complex home healthcare planning.
• Enhanced understanding of decomposition strategies for optimization in healthcare logistics.