Improved Average Penalty Cost (IAPC) Method to Obtain Initial Basic Feasible Solution of Transportation Problem

Authors

  • Md. Munir Hossain

transportation table (TT), IBFS, VAM, LCM

Abstract

Operational planning, scheduling and synchronization of all production activities are the key responsibilities of the management of a manufacturing plant. Transport modeling is one such activity which is directly involved in the production cost. Therefore, it is necessary for the management of the plant to design the transportation process in such way so that the total production cost is minimized, subject to the constraint that cannot be compromised. In the solution procedure of these transportation problems, an initial basic feasible solution (IBFS) is always require to reach at the optimal solution. In this study, a new algorithm is developed to find IBFS. The result of the proposed method is compared with more classical method naming Vogel's Approximation Method (VAM) and cost cell based method named Least Cost Method (LCM). Here the number of numerical problems is established and found in 58.3% cases the proposed method provides optimal where the rest of the cases it offers very near to optimal solution. For finding the degree of effectiveness of proposed method a study is carried out and simulation results show that Improved Average Penalty Cost (IAPC) yields better IBFS than VAM and LCM.

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How to Cite

Improved Average Penalty Cost (IAPC) Method to Obtain Initial Basic Feasible Solution of Transportation Problem. (2020). Global Journal of Science Frontier Research, 20(F8), 23-36. https://www.journalofscience.org/index.php/GJSFR/article/view/2848

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Improved Average Penalty Cost (IAPC) Method to Obtain Initial Basic Feasible Solution of Transportation Problem

Published

2020-12-15

How to Cite

Improved Average Penalty Cost (IAPC) Method to Obtain Initial Basic Feasible Solution of Transportation Problem. (2020). Global Journal of Science Frontier Research, 20(F8), 23-36. https://www.journalofscience.org/index.php/GJSFR/article/view/2848