  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.
