Route Planning for Intra-Hospital Patient Transportation Using Metaheuristics and Mixed Integer Linear Programming

Area of Science:

• Healthcare Operations Research
• Logistics Optimization
• Hospital Management Systems

Background:

• Healthcare services involve complex processes impacting patient care quality.
• Patient transportation, both inter- and intra-hospital, is a critical logistical challenge.
• Existing intra-hospital transportation route planning faces complexities from dynamic factors and fairness considerations.

Purpose of the Study:

• To determine the optimal number of transporters required for intra-hospital patient transport.
• To generate efficient route plans for all transporters, distributing jobs within shifts.
• To minimize total travel time, idle time, and travel time deviations among transporters.

Main Methods:

• Utilized multi-staged Local Search Metaheuristics for primary objective achievement.
• Integrated Mixed Integer Linear Programming for fair job allocation and constraint formulation.
• Incorporated optimization constraints to satisfy secondary objectives, including minimizing travel and idle times.

Main Results:

• Successfully determined feasible numbers of transporters and generated optimized route plans.
• Achieved significant reductions in total travel and idle times for transporters.
• Demonstrated minimized deviations in total travel time across all transporters, ensuring workload fairness.
• The optimization constraints effectively balanced multiple objectives in route planning.

Conclusions:

• The proposed multi-staged Local Search Metaheuristics with Mixed Integer Linear Programming offers a robust solution for intra-hospital patient transportation.
• The method enhances the efficiency and fairness of patient transport logistics within hospitals.
• This approach leads to improved healthcare service quality through optimized resource allocation and reduced operational inefficiencies.