FerielFerhi/NAFTAL-Fuel-Depot-Optimization

Bi-objective optimization for fuel depot location — NAFTAL Algeria | NSGA-II, Python, CPLEX | 13 warehouses, 629 service stations # Fuel Depot Location Optimization — NAFTAL Algeria ## 🔍 Problem NAFTAL, Algeria's national fuel distribution company, faced insufficient storage capacity across its network. The goal was to determine the optimal placement of new storage tanks to cover the national market. ## 🎯 Objectives - **Minimize** total costs (installation + storage + transport) - **Maximize** storage capacity across warehouses ## 📊 Problem Scale - 13 warehouses across Algeria - 629 service stations - 16,588 decision variables - 1,320 constraints ## ⚙️ Methods Used - Integer Linear Programming (IBM CPLEX) - NSGA-II — Non Dominated Sorting Genetic Algorithm II - Greedy Heuristic for initial solution construction - Google Earth Pro for geographic data extraction ## 🛠️ Tools & Languages - Python (NumPy, Pandas, Requests, Itertools) - IBM CPLEX / OPL - Google Earth Pro - Google Maps API (distance calculation) ## 📝 Full Report Available upon request.