  This paper considers an extension of the vehicle routing problem with
synchronization constraints and introduces the vehicle routing problem with
multiple synchronization constraints and variable service time. This important
problem is motivated by a real-world problem faced by one of the largest
agricultural companies in the world providing precision agriculture services to
their clients who are farmers and growers. The solution to this problem impacts
the performance of farm spraying operations and can help design policies to
improve spraying operations in large-scale farming. We propose a Mixed Integer
Programming (MIP) model for this challenging problem, along with
problem-specific valid inequalities. A three-phase powerful matheuristic is
proposed to solve large instances enhanced with a novel local search method. We
conduct extensive numerical analysis using realistic data. Results show that
our matheuristic is fast and efficient in terms of solution quality and
computational time compared to the state-of-the-art MIP solver. Using
real-world data, we demonstrate the importance of considering an optimization
approach to solve the problem, showing that the policy implemented in practice
overestimates the costs by 15-20%. Finally, we compare and contrast the impact
of various decision-maker preferences on several key performance metrics by
comparing different mathematical models.
