Optimal Truck-Tank Assignment for Compressed Natural Gas Delivery: A Case Study from Vietnam

This paper addresses the scheduling problem for Compressed Natural Gas (CNG) delivery using a case study from Vietnam. We develop a dynamic Mixed-Integer Linear Programming (MILP) model to optimize the assignment of trucks and tanks, minimizing costs while respecting practical constraints like resource capacities, variable customer demand, and delivery timing. Experiments using real-world data show the MILP model achieves optimal solutions satisfying all constraints within practical computation times. A comparison with a Genetic Algorithm (GA) highlights MILP's superior precision and constraint adherence, crucial for CNG logistics, although GA offers faster approximate solutions. This research demonstrates the value of MILP for optimizing energy distribution logistics.