Abstract

This paper discusses the optimization of the Capacitated Warehouse Location Problem (CWLP) under uncertain demand and supply. We propose an optimization framework that addresses the CWLP by considering blood distribution to identify optimal blood center locations. The objective is to meet all blood orders at the lowest possible cost, subject to warehouse capacity constraints. This study applies the framework to cities in the Kingdom of Saudi Arabia with high demand for blood delivery. We utilized census data from selected cities, with a representative sample of each city designated as a customer base. A novel mixed-integer linear programming (MILP) model was developed and solved using Python to determine the minimum total transportation and fixed costs for blood center construction. The proposed warehouse locations are presented on a map, showing each city connected to its optimal blood center warehouse.

Key words: Keywords: Mixed Integer Linear Programming; Capacitated Warehouse Location Problem; Optimization.