Optimizing transportation cost by using linear programming

Effective transportation planning is critical for businesses to reduce operational costs, improve distribution efficiency, and increase overall profitability. To optimized transportation costs in a roadbased distribution system, this study applies Linear Programming (LP), a mathematical technique that produces the most effective results under specified constraints. The study used secondary data which is based on a case study of the Yusril Medan Bread Distribution business and involves two supply centers and four demand areas. The data set consists of supply capacities, demand requirements and unit transportation costs between supply and demand points. To find the most cost-effective method for distributing goods, a transportation model was created and solved with LINGO software. The results were compared with the Minimum Cell Cost Method (MCCM), a commonly used heuristic in transportation planning. The LP approach achieved a total transportation cost of RM39.05, while MCCM produced a higher cost of RM42.00. These results show how effective LP is at helping balanced supply demand fullfilment, reducing distribution costs, and enhancing resource utilisation. This study additionally illustrates how important it is to integrate optimisation tools into logistics decision-making to enhance operational performance.