The rapid expansion of the e-grocery market has led to significant challenges in last-mile delivery, par- ticularly in managing heterogeneous fleets, accommodating multiple capacity constraints, and adhering to strict time windows. This paper introduces TOET (Tailored Optimisation for E-grocery Transport), a novel framework that addresses these issues through advanced metaheuristic techniques, dynamic hyperparameter tuning, and specialized arrival time calculations. Benchmark experiments on real-world dispatch plans demonstrate that while TOET variants substantially reduce runtime and drive time, the benchmark VROOM algorithm still excels at minimizing the number of routes, revealing a trade-off between drive time and fleet utilization. Overall, TOET shows promise for enhancing operational efficiency and sustainability in e-grocery logistics. Future work will refine arrival time strategies, improve scalability, and conduct an economic and environmental impact analysis of the trade-off between drive duration and route consolidation.