Optimizing Service Throughput in Heterogeneous Traffic Streams: A Discrete-Event Simulation of Subsidized Energy Distribution
Abstract
In the context of developing urban logistics, the distribution of subsidized energy is often constrained by stochastic demand and significantly heterogeneous vehicle streams—specifically motorcycles versus automobiles—which frequently results in unbalanced server utilization and high customer balking rates. This study aims to optimize service throughput by evaluating the operational performance of segregated versus pooled queuing configurations through a discrete-event simulation (DES) approach. Validated against empirical arrival data (N = 2,329 entities) from a high-volume refueling node modeled as a general queuing network (approx. M/G/2), the research contrasts a rigid dedicated-lane model against a proposed flexible resource-pooling model. Simulation results demonstrate that the resource-pooling configuration significantly outperforms traditional segregated designs in high-density scenarios, achieving a balanced server utilization rate and successfully eliminating customer balking probability. Furthermore, the pooled strategy reduced average waiting times for large vehicles by 52.8%, providing empirical evidence that facility managers in mixed-traffic environments should prioritize dynamic server allocation over rigid physical segregation to maximize service accessibility and operational efficiency.
How to Cite This Article
Sriyanto, Yudha Arif Budiyani, M Mujiya Ulkhaq (2025). Optimizing Service Throughput in Heterogeneous Traffic Streams: A Discrete-Event Simulation of Subsidized Energy Distribution . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 6(6), 883-886.
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