This research intends to develop a new algorithm for the initial basic feasible solution (IBFS) to get an optimal solution (best solution) to a transportation problem (TP). One of the key concepts of linear programming problems is a transportation problem. In the transportation model, multiple commodities are transported from one source to one destination at the lowest possible cost. Every organization's motivation is to identify the shortest route and reduce the cost or time. Developing a new algorithm is a crucial step in achieving the optimal solution. A novel initial basic feasible solution based on supply-demand cost conditions and Vogel's approximation method (VAM) combines and minimizes the cost of TP it requires fewer iterations to reach the optimum solution. To check the non-degeneracy condition or optimality a UV technique is performed. MATLAB is a programming tool developed to analyze and design systems to give exact results. We used MATLAB software to run both the initial and optimum solution. A few numerical examples were used to implement the suggested technique. The results are compared with other existing methodologies. The proposed method incorporates balanced and unbalanced issues, which produce more effective outcomes.