Paper Contents
Abstract
Public rail transportation is a vital component of Malaysias urban mobility system, particularly in the Klang Valley, where millions rely on LRT, MRT, and KTM services daily. However, frequent delays, lengthy interchange routes, and inefficient scheduling reduce service quality and passenger satisfaction. This study proposes a metaheuristic-based route optimization system SmartRail.Co to improve efficiency through multi-criteria optimization considering distance, time, and cost. Using a dynamic visualization and user-interactive interface developed via Streamlit, the system provides real-time optimal route suggestions on uploaded maps. Comparative analysis among different metaheuristic algorithms demonstrates superior adaptability and performance in handling complex rail network data. The proposed approach supports Malaysias sustainable urban transport goals aligned with SDG 8, 9, 11, and 17, promoting smarter, greener, and more inclusive mobility.
Copyright
Copyright © 2025 Suliadi Firdaus Sufahani. This is an open access article distributed under the Creative Commons Attribution License.
