Transportation Problem: Northwest Corner Method & Linear Programming Formulation

Published on May 28, 2026

Linear-Algebra

Solve a transportation problem using the Northwest Corner Method to find the minimum shipping cost and formulate it as a linear programming problem.

Question

Answer

Based on the provided image, here is the step-by-step solution for Question One.

Question One Solution

Given Data:
  • Supplies (Factories):
    • Factory A: boxes
    • Factory B: boxes
    • Total Supply = boxes
  • Demands (Retailers):
    • Retailer 1: boxes
    • Retailer 2: boxes
    • Retailer 3: boxes
    • Total Demand = boxes
  • Unit Shipping Costs (Tanzania shillings per box):
    Factory Retailer 1 Retailer 2 Retailer 3
    A 14 13 11
    B 13 13 12

(a) Northwest Corner Method

The Northwest Corner Method starts allocations from the top-left cell and moves right or down as supply/demand is exhausted.
  1. Cell (A, 1): Demand for Retailer 1 is , Supply from A is . Allocate .
    • Retailer 1 demand is satisfied.
    • Remaining supply at A: .
  2. Cell (A, 2): Demand for Retailer 2 is , Remaining supply from A is . Allocate .
    • Factory A supply is exhausted.
    • Remaining demand for Retailer 2: .
  3. Cell (B, 2): Remaining demand for Retailer 2 is , Supply from B is . Allocate .
    • Retailer 2 demand is satisfied.
    • Remaining supply at B: .
  4. Cell (B, 3): Demand for Retailer 3 is , Remaining supply from B is . Allocate .
    • All demands and supplies are satisfied.
Shipping Schedule:
  • Factory A Retailer 1: boxes
  • Factory A Retailer 2: boxes
  • Factory B Retailer 2: boxes
  • Factory B Retailer 3: boxes
Total Cost Calculation:

(b) Linear Programming Formulation

Let be the number of boxes shipped from Factory (where ) to Retailer (where ).
Objective Function:
Minimize the total shipping cost :
Constraints:
  1. Supply Constraints:
    • (Factory A)
    • (Factory B)
  2. Demand Constraints:
    • (Retailer 1)
    • (Retailer 2)
    • (Retailer 3)
  3. Non-negativity Constraints:
    • for all and .