A two-phase vehicle based decomposition algorithm for large-scale capacitated vehicle routing with time windows

With significant advances in computing power during recent years, increasingly complex variants of the vehicle routing problem (VRP) with added constraints are coming into focus. VRP is a combination of the classical traveling salesman and bin packing problems, with many real world applications in various fields - from physical resource manipulation planning to virtual resource management in the ever more popular cloud computing domain. In this paper, we consider large-scale VRP problem instances with time window constraints. Due to their complexity, we propose a solution approach based on the divide and conquer paradigm, decomposing problem instances into smaller, mutually independent sub-problems which can be solved using traditional algorithms and integrated into a global solution of reasonably good quality. Numerical results indicate the efficiency and scalability of the proposed approach, making it highly applicable to large-scale realistic VRP problem instances.