Machine scheduling;
Flow-shop problem;
Parallel batching;
Hospital operations;
SDG 3 Good health and well-being;
PARALLEL BATCHING MACHINES;
REUSABLE INSTRUMENTS;
GENETIC ALGORITHM;
SHOP;
SETUP;
JOBS;
OPTIMIZATION;
DEVICES;
COSTS;
TIMES;
D O I:
10.1016/j.eswa.2024.125624
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
Sterile processing is a critical secondary process and a major cost factor in the processing, acquisition, and storage of costly medical devices. This article aims to improve the performance of sterile processing by developing, implementing, and evaluating a dispatching rule-based algorithm to reduce the time medical devices spend in the central sterile supply department using a two-stage hybrid flow-shop formulation. The algorithm combines dispatching rules with stage decomposition and compatibility conditions. A genetic algorithm is designed to benchmark the performance in addition to an analytic bound. Real-world data from a large German hospital were used to test the effectiveness of the heuristics. The case study demonstrated the practical implications of the approach, leading to a reduction in the time medical devices spend in the system and improved utilization of washer-disinfector machines and sterilizers. It also highlighted the importance of aligning machine capacity with demand and the potential trade-offs associated with batch processing decisions. Our approach can contribute to substantial operational cost savings and efficiency gains, offering significant benefits to decision makers at both the operational and tactical levels.