Apply for ant colony optimization (ACO) algorithm for vehicle routing problem with time windows in food industry: The case of food distribution company

Abstract

Apply Ant Colony Optimization (ACO) this paper studied about the vehicle routing problem with time windows (VRPTW) in food industry which main products are perishable and short lifespan. In Vietnam, there has a sustainable growth in this area that requires expanding more in the distribution network of companies. Thus, the logistics systems are operated under pressure to be more speedy and more reliable with time requirements. In this study, it proposed two solving methods which aim to find optimal route in delivery. The main objective is to minimize the total cost which include both shipping and penalty cost. In the first method, a mix integer programming (MIP) model is developed to find exact solution by branch-and-bound methods. The results are collected by CPLEX. In the second one, meta-heuristics is applied to find optimal solution to be Ant Colony Optimization (ACO), the result is provided by Python. The study also takes in to account the constraints about two types of vehicles for different traveling distance. The real data of steamy foods in Vietnam is applied for computation tests. The results showed the exact method provide better solution than meta-heuristics one. However, it is taken more computation time and limited the number of customers.