Deterministic Model-Based Simulation for Optimizing Bus Company Operations

Alfito Zakaria, Muhammad Ainul Yaqin

Abstract


This research addresses the optimization of operational routes within bus companies, with a particular focus on reducing fuel costs and travel times. The importance of this study lies in its relevance to enhancing the efficiency of transportation systems, which is crucial for cost management and service quality in the bus industry. The primary objective of this research is to explore how deterministic simulation models can be employed to improve operational efficiency in bus companies. Specifically, the study investigates the impact of changes in routing and scheduling on fuel consumption and travel duration. To achieve this, a deterministic simulation model was developed using Google Spreadsheet, featuring Scenario Manager integration for "what-if" analysis. Data was collected from literature reviews and datasets available on Kaggle, encompassing key parameters such as routes, distances, fuel consumption, travel times, and operational schedules. The results of the simulation indicate that implementing alternative routes and adjusting schedules can lead to a significant reduction in fuel costs by as much as 12% and travel time by up to 15%. These findings underscore the effectiveness of deterministic simulation in enhancing the operational efficiency of transportation systems. This study demonstrates that deterministic simulation serves as a valuable tool for optimizing route allocation and resource utilization within bus companies. Future research should consider integrating real-time data and advanced optimization techniques, such as machine learning algorithms, to further refine operational strategies.

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References


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DOI: https://doi.org/10.18860/jocdas.v2i2.30408

DOI (PDF): https://doi.org/10.18860/jocdas.v2i2.30408.g12111

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