Optimising Waste Management Collaboration Processes Using Hybrid Modelling

The high amount of hazardous medical waste involves high risks, so optimising waste management processes is crucial. Some research proposes hybrid modelling that combines simulations and operation research approaches, and most hybrid modelling methods focus on optimising waste transport routes. This...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of simulation modelling Vol. 23; no. 1; pp. 53 - 64
Main Authors Sungkono, K. R., Sarno, R., Onggo, B. S., Septiyanto, A. F.
Format Journal Article
LanguageEnglish
Published Vienna DAAAM International Vienna 01.03.2024
Subjects
Collaboration
Cooperation
Discrete event systems
Hazardous wastes
Medical wastes
Modelling
Optimization
Overloading
Simulation
Waste management
Online AccessGet full text

Cover

More Information
Summary:The high amount of hazardous medical waste involves high risks, so optimising waste management processes is crucial. Some research proposes hybrid modelling that combines simulations and operation research approaches, and most hybrid modelling methods focus on optimising waste transport routes. This paper proposes hybrid modelling to optimise the number of workers with minimum asynchronous waiting time (AWT) and activity costs based on waste management collaboration processes. Hybrid modelling consists of an integrated discrete-event simulation, agent-based simulation and improved MCDM methods (MOORA and COPRAS). The cases of waste management processes under normal and overload conditions verify the performance of the proposed hybrid modelling. Improved MCDM methods save 27 % of MCDM processing time. The AWT and activity cost under normal condition using the hybrid modelling decreased by 38 % and 22 %, respectively. Hybrid modelling can minimise 74 % AWT and 31 % activity cost compared to the actual model under an overload condition. MOORA is better when reducing activity cost, and COPRAS is better when minimising AWT.
ISSN:1726-4529
1726-4529
DOI:10.2507/IJSIMM23-1-671