This online video lecture explained Vogel’s Approximation Method (VAM) for Transportaion Problem for #MTH601 Students of #VU and BSIT, BSCS and BSSE stduents of #GCUF in #Urdu and Hindi.
Vogel’s Aproximation Method
This method is based on the ‘difference’ associated with each row and column in the matrix giving unit cost of transportation cij. This ‘difference’ is defined as the arithmetic difference between the smallest and next to the
smallest element in that row or column. This difference in a row or column indicates the minimum unit penalty incurred in failing to make an allocation to the smallest cost cell in that row or column. This difference also provides a measure of proper priorities for making allocations to the respective rows and column.
Steps of Vogel’s Approximation Method
A summary of the steps involved in Vogel’s Approximation Method is given below:
- STEP 1: Represent the transportation problem in the standard tabular form.
- STEP 2: Select the smallest element in each row and the next to the smallest element in that row. Find the
- difference. This is the penalty written on the right hand side of each row. Repeat the same for each column. The
- penalty is written below each column.
- STEP 3: Select the row or column with largest penalty. If there is a tie, the same can be broken arbitrarily.
- STEP 4: Allocate the maximum feasible amount to the smallest cost cell in that row or column.
- STEP 5: Allocate zero else where in the row or column where the supply or demand is exhausted.
- STEP 6: Remove all fully allocated rows or columns from further consideration. Then proceed with the remaining
- reduced matrix till no rows or columns remain.
Transportation Problem Solution by Vogel’s Approximation Method Video in Urdu and Hindi
Key Topics of the Video are
- What is Transportation Problem?
- What are different Transportation Problem Solution methods?
- What is Vogel’s Approximation method?
- Steps of Vogel’s approximation method?
- How to calculate Row and Column Penalty?
- Comparison of NWC, LCM and VAM