Standard Operating Procedure Optimization of Resource Level for Hospital Waste Handling Using Hybrid DES-ABM Simulation, Genetic Algorithm, and Goal Programming
- DOI
- 10.2991/aebmr.k.211226.012How to use a DOI?
- Keywords
- hospital resource; optimization; simulation; waste
- Abstract
The emergence of the Covid-19 pandemic has caused several changes in healthcare services carried out by hospitals. Covid-19 has caused increasing waste generated from medical activities and operational service activities, in which the Standard Operating Procedure (SOP) has been adjusted due to new regulations to prevent cross-contamination during this pandemic. The increasing number of wastes generated and changes in SOP could have impacted on spending more costs for processing medical waste caused by Covid-19 operational services and causes longer service time. The purpose of this study was to find the optimum value of resource level based on operational costs and service time from the medical waste handling developed with hybrid Discrete Event Simulation – Agent-Based Modelling (DES-ABM) to capture real-time events. To find optimum value, optimization techniques such as Genetic Algorithm and Goal Programming are also used. Optimization from this research results in 17 alternatives of resource level from a total of 100 generations and 20 initial design point. The best design point found could reduce the waiting time by 26.87 minutes, reduce completion time by 506.82 minutes, and reduce cost IDR117,144 from the initial resource level used by the hospital.
- Copyright
- © 2021 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Danica Virlianda Marsha AU - Riyanarto Sarno AU - Kelly Rossa Sungkono PY - 2021 DA - 2021/12/31 TI - Standard Operating Procedure Optimization of Resource Level for Hospital Waste Handling Using Hybrid DES-ABM Simulation, Genetic Algorithm, and Goal Programming BT - Proceedings of the 3rd International Conference on Business and Management of Technology (ICONBMT 2021) PB - Atlantis Press SP - 87 EP - 94 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.211226.012 DO - 10.2991/aebmr.k.211226.012 ID - Marsha2021 ER -