A hybrid algorithm for the Vehicle Routing Problem with AND/OR Precedence Constraints and time windows

In this research, a new variant of the vehicle routing problem with time windows is addressed. The nodes associated with the customers are related to each other through AND/OR precedence constraints. The objective is minimizing the total traveling and service time. This generalization is necessary for problems where the visiting node sequence is defined according to the AND/OR relations, such as picker routing problems. We propose a Mixed Integer Linear Programming model to solve small-scale instances extended from the well-known Solomon benchmark. A meta-heuristic algorithm based on the hybridization of Iterated Local Search and Simulated Annealing approaches is developed, which can compute reasonable solutions in terms of CPU time and the accuracy of solutions. To improve the hybrid algorithm's performance, the Taguchi method is used to tune the algorithm parameters. A comprehensive computational analysis is conducted to analyze the performance of the proposed methods.