Optimizing Transportation Cost Using Linear Programming: A Malaysian Case Study

Abstract

This paper aims to review the linear programming methods used by Karsh R. Shah to solve the transportation problem faced by MITCO Labuan Company Limited (MLCL). In Karsh R. Shah’s study, the Vogel’s Approximation Method (VAM) and Modified Distribution (MODI) method were adopted to identify the best polymer materials distribution plan that gives the optimal shipping cost from four Petronas manufacturing plants to four demand destinations. The current study re-created the network representation, mathematical model, and spreadsheet models as comparisons. For determining the initial BSF, the North West Corner Method (NWCM) and VAM are used. Subsequently, the sensitivity analysis is used to analyze the impact of uncertainty of unit shipping costs on the company's total transportation costs. When compared to VAM, the shipping cost of the initial basic feasible solution through NWCM is the lowest, hence, it is tested for optimality using the simplex method (using Excel Solver). The optimum shipping cost obtained from this solution is RM120,000million. The sensitivity analysis developed in this study will further help MLCL in identifying the balance and range of production capacity, without affecting the optimal solution. Ultimately, this study has evidenced that the application of linear programming in an organization increases the effectiveness and efficiency of its operations, allowing organizations to maximize profits while minimizing costs.