Week 4 BUSN 312 Homework

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American Military University *

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Industrial Engineering

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Feb 20, 2024

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Week 4 Assignment: Transportation Problem John DOe American Military University COURSE BUSN312: Operations Research DR. Matasha Murrell Murrell Jones 28 May 2023
1. Find the minimum cost solution for the following transportation problem which has cost structure as: To/From P Q R Availabili ty A 16 19 12 14 B 22 13 19 16 C 14 28 18 12 Requirem ent 10 15 17 The first step is to find the cell with the lowest cost, which in this case is the cell (A, R) with a cost of 12. Next, we allocate the maximum possible quantity to the cell (A, R) based on the minimum value of availability and requirement (14 availability/17 requirement), in this case is 14. The next step is to update the availability and requirement values based on the allocation made. Finally, since the availability of 14 has been exhausted, the rest of row A can be eliminated as shown below: To/From P Q R Availabili ty A 16 19 12 14 14 0 B 22 13 19 16 C 14 28 18 12 Requirem ent 10 15 17 3 The above steps are repeated choosing the following available lowest cost, which in this case is cell (B, Q) with a value of 13. The updated table is shown below: To/From P Q R Availabili ty
A 16 19 12 14 14 0 B 22 13 15 19 16 1 C 14 28 18 12 Requirem ent 10 15 0 17 3 After all the supply and demand values have been exhausted, the table is completed as follows: To/From P Q R Availabili ty A 16 19 12 14 14, 0 B 22 13 15 19 1 16, 1 , 0 C 14 10 28 18 2 12, 2 , 0 Requirem ent 10 0 15 0 17 3, 1 , 0 The transportation cost is then calculated by performing a multiplication of the individual combinations and adding all values: TC= (14x12) + (15 x 13) + (10 x 14) + (2 x 18) + (1 x 19) TC= 168 + 195 + 140 + 36 + 19, that equals 558. 2. Briefly describe the Simplex method, Goal Programming, and Integer Programming. The Simplex method is an algorithm used to solve linear programming problems. An approach that improves the solution until an optimal solution is reached. The method starts with an initial feasible solution and then iteratively moves to adjacent feasible solutions that improve the objective function value. The algorithm continues until no further improvement is possible, indicating the optimal solution. The Simplex method is popular due to its efficiency and effectiveness in solving linear programming problems. Goal Programming is an optimization technique to solve problems with conflicting objectives or goals. Unlike traditional linear programming, where there is a single objective to
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