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Informative Article | Science and Technology | India | Volume 9 Issue 9, September 2020 | Popularity: 5.3 / 10
Navigating Complexity: Smart Solutions for School Bus Route Optimization
Aditya Kumar Sharma
Abstract: This research paper explores a holistic and data - driven methodology for optimizing school bus routes, presenting a comprehensive framework designed to enhance efficiency, safety, and inclusivity in student transportation systems. The paper provided a step - by - step process of the best ways to optimize school routes through location - related data, using machine learning algorithms to identify optimal bus stop locations and integrating that with the GIS analysis to ensure strategic placements and streamlined routing. Advanced techniques, notably K - Means clustering, introduce a sophisticated layer to school distribution optimization. Validation mechanisms and the fusion of linear regression can refine bus stop optimization and emphasize continuous improvement through real - time data updates. Tiers creation, bell time optimization, and the implementation of staggered bell times contribute to further operational efficiency gains. Strategies like mixed riding and Loading exemplify a commitment to inclusivity, resource optimization, and cost efficiency. The paper culminates in a robust route optimization model, amalgamating clustering, regression, and dynamic adjustments, leading to a responsive and effective school commute system. This research provides a nuanced and detailed approach to designing optimized school bus routes, incorporating spatial analysis, clustering algorithms, regression models, and dynamic strategies. The proposed model is a comprehensive guide for school administrators and transportation planners, ensuring operational excellence, safety adherence, and adaptability to diverse and evolving student transportation needs.
Keywords: School bus routing, transportation optimization, route planning, geographic clustering, K - Means clustering, linear regression, mixed riding, staggered bell times, vehicle scheduling, routing algorithms, resource optimization, school transportation efficiency
Edition: Volume 9 Issue 9, September 2020
Pages: 1598 - 1606
DOI: https://www.doi.org/10.21275/SR24212154915
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