Enhancing Transportation Efficiency and Sustainability through Robust Optimization Models

Gerald Imbugwa, Tom Gilb, Manuel Mazzara

Keywords: Last-mile carpooling, optimization model, travel time, cost reduction, branch-and-bound algorithm, transit-based ridesharing, urban mobility.

Abstract:

This paper presents a mathematical model and experimentation, for carpooling and micromobility. Our aim is to addresses the problem of urban traffic congestion, the model focusses on route optimization, operational cost reduction, and overall service quality improvement. In order to provide cost effective and time efficient solutiion, the model tests takes into account a wide range of scenarios, including peak hours, off-peak hours, adverse weather conditions, special events, and accidents.

The experiment's findings clearly show significant progress in each of the investigated conditions. During peak hours, the model was able to achieve an objective value of 1217.88 by utilizing 34 micromobility trips and 56 multi-leg journeys. In the off-peak hours, there were 33 micromobility trips and 57 multi-leg excursions, which resulted in an increased objective value of 1070.21. The objective value remained unchanged at 1181.04 throughout the scenarios that included adverse weather conditions, special events, and accidents. We achieved this by maintaining consistent micromobility and multi-leg trip distributions. The model effectively enhances the operational efficiency and sustainability of transport networks, as demonstrated by this set of findings.

To further improve the model, future study topics can benefit from the introduction of new technology, such as autonomous vehicles and real-time data analytics. The studies by integrating these technologies into our model can improve time efficiency, cost, low CO2 emissions and service quality. We propose that industry stakeholders and academic institutions collaborate and promote this industry, encourage innovation, and produce environmentally friendly transportation solutions that improve the quality of life for people all over the world.

Submission Number: 5