<p>Optimising the allocation of resources from “m” supply sources to “n” demand locations is the goal of a Transportation Problem (TP), which tries to maximise operational efficiency while considering variable costs attached to delivering commodities. Many studies in this field have focused on finding ways to reduce shipping costs, delivery times, and distance. The decision-making situations in multi-objective transportation problems (MOTP) are more intricate since they incorporate numerous objectives. Looking at three case studies with one, two, and three objectives, this paper covers several strategies applied in MOTP. The results show that the suggested method achieves a transport cost of 2968, which is far better than both contemporary single-objective and multi-objective traffic algorithms. Additionally, as compared to other approaches, ours not only improves logistics operations’ overall efficiency by cutting down on transit time and fuel usage, but it also provides decision-makers with a wider range of ideal solutions.</p>