What does this research mean for the field?

A hybrid optimization framework integrating Ant Colony Optimization, Bacterial Swarm Optimization, and Deep Reinforcement Learning (ACO-BSO-DRL) significantly reduces required fleet size, improves energy efficiency, and achieves faster, more stable convergence in shared electric vehicle systems compared to standalone methods. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The aim is to enhance the efficiency and sustainability of shared electric vehicles by optimizing fleet size, routing, and energy management.

April 18, 2026Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering

Integrated fleet sizing and routing optimization for shared electric vehicles under energy and charging constraints

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Authors

VRVijay Raviprabhakaran

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Implication

This framework optimizes fleet sizing and routing in shared electric vehicles, indicating significant sustainability benefits.

Key Points

The aim is to enhance the efficiency and sustainability of shared electric vehicles by optimizing fleet size, routing, and energy management.
Developed a hybrid optimization framework combining ACO, BSO, and DRL.
Modeled urban transportation networks as constrained graphs.
Used simulations based on realistic urban scenarios in Hyderabad and Bengaluru.
Conducted a comparative analysis with other metaheuristic and learning-based methods.
Performed multi-run statistical evaluations to assess robustness.
Achieved consistent reductions in required fleet size.
Improved energy utilization efficiency.
Demonstrated faster and more stable convergence of the optimization algorithm.
Confirmed the robustness and repeatability of the approach under randomized conditions.
Showed significant potential for enhancing the sustainability of shared electric mobility systems.

Cite This Study

Vijay Raviprabhakaran (2026) studied this question.

synapsesocial.com/papers/69e3205140886becb653f5e4 https://doi.org/10.1177/09544070261440372

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Integrated fleet sizing and routing optimization for shared electric vehicles under energy and charging constraints

Discussion

Member takes

Implication

Key Points

Cite This Study

Integrated fleet sizing and routing optimization for shared electric vehicles under energy and charging constraints

Discussion

Member takes

Implication

Key Points

Cite This Study

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