TY - JOUR
T1 - Optimization of time and cost of multi organization business processes in a port container terminal
AU - Fajar, Aziz
AU - Sarno, Riyanarto
N1 - Publisher Copyright:
© 2019 Intelligent Network and Systems Society.
PY - 2019
Y1 - 2019
N2 - Port Container Terminal (PCT) involves multi organizations whiAR are Customer, PCT, Custom, and Quarantine. The business processes of those organizations interact asynARronously from container arrivals to the release of the containers. An organization can be handled by multi agents, whiAR represent the actors involved to perform a sequence of activities (tasks) in the organization. AsynARronous Waiting Time (AWT) occurs when an agent assigns a task to another agent whiAR is still working on another task. The previous study discovered that AWT contributes a significant amount of time. Therefore, this researAR proposes a method to reduce the AWT by parallelizing the agents of an organization and simulating the parallelized agents using agent based simulation. The simulation results time and cost are then optimized using three methods namely StoARastic Multi-Criteria Adaptability Analysis-2 (SMAA-2), Multi Objective Optimization on the Basis of Ratio Analysis (MOORA), and Complex Proportional Assessment (COPRAS). The three methods aARieve the same reduced AWT to 9.4%. From those methods, MOORA aARieves the highest accuracy of 80% and the sensitivity coefficient of 7. However, COPRAS results in 78% accuracy with lower sensitivity coefficient of 6. SMAA-2 results in the lowest accuracy of 40% and the highest sensitivity coefficient of 13.
AB - Port Container Terminal (PCT) involves multi organizations whiAR are Customer, PCT, Custom, and Quarantine. The business processes of those organizations interact asynARronously from container arrivals to the release of the containers. An organization can be handled by multi agents, whiAR represent the actors involved to perform a sequence of activities (tasks) in the organization. AsynARronous Waiting Time (AWT) occurs when an agent assigns a task to another agent whiAR is still working on another task. The previous study discovered that AWT contributes a significant amount of time. Therefore, this researAR proposes a method to reduce the AWT by parallelizing the agents of an organization and simulating the parallelized agents using agent based simulation. The simulation results time and cost are then optimized using three methods namely StoARastic Multi-Criteria Adaptability Analysis-2 (SMAA-2), Multi Objective Optimization on the Basis of Ratio Analysis (MOORA), and Complex Proportional Assessment (COPRAS). The three methods aARieve the same reduced AWT to 9.4%. From those methods, MOORA aARieves the highest accuracy of 80% and the sensitivity coefficient of 7. However, COPRAS results in 78% accuracy with lower sensitivity coefficient of 6. SMAA-2 results in the lowest accuracy of 40% and the highest sensitivity coefficient of 13.
KW - Agent based simulation
KW - Business process prallelization
KW - Copras
KW - Moora
KW - Simulation
KW - Smaa-2
UR - http://www.scopus.com/inward/record.url?scp=85077863649&partnerID=8YFLogxK
U2 - 10.22266/ijies2019.1231.25
DO - 10.22266/ijies2019.1231.25
M3 - Article
AN - SCOPUS:85077863649
SN - 2185-310X
VL - 12
SP - 259
EP - 271
JO - International Journal of Intelligent Engineering and Systems
JF - International Journal of Intelligent Engineering and Systems
IS - 6
ER -