Sustainable development is embraced by many groups for economic growth, environmental preservation, and social equality. This work presents a Tabu Search approach for minimising Sustainable-cost in the Single Depot Vehicle Routing Problem with Time Windows (VRPTW) with a heterogeneous fleet of vehicles. Tabu Search was given five greedy heuristic algorithms such as SAVING, SWEEP, NNH-1, NNH-2, and CIH, a random algorithm, and its sustainable variations as initial input. The algorithms were tested on the benchmark datasets of Solomon, Gehring, and Homberger, as well as a randomly generated dataset. Various computational analyses performed using Relative Percentage Deviation and Kruskal Wallis-H test indicates that the Tabu search algorithm tries to minimize the sustainable cost obtained from these initial solutions. TS-S-SAVING relatively and consistently outperforms in terms of the different performance measures considered in this study by attaining an efficiency of 96.55% for the benchmark dataset and 100% for the instance generated datasets.