I have a dataset containing cities, the distances of warehouses from each city, and the load capacities. My task is to optimize the number of warehouses assigned to each city to minimize costs.
The optimization should consider both load and distance. For example:
a. If both the distance and load are small, the warehouse should not be considered.
b. If both the distance and load are large, the warehouse should be considered.
c. If the distance is small but the load is large, the warehouse should be preferred.
d. Zero or void cases should be neglected.
This optimization needs to be performed using permutation and combination concepts.
I will close this thread since there is another one with the exact same content by Priyanka Natarajan but includes a workbook.
