A hybridisation of adaptive variable neighbourhood search and large neighbourhood search: Application to the vehicle routing problem

In this paper, an adaptive variable neighbourhood search (AVNS) algorithm that

incorporates large neighbourhood search (LNS) as a diversification strategy is proposed

and applied to the capacitated vehicle routing problem. The AVNS consists

of two stages: a learning phase and a multi-level VNS with guided local search.

The adaptive aspect is integrated in the local search where a set of highly successful

local searches is selected based on the intelligent selection mechanism. In

addition, the hybridisation of LNS with the AVNS enables the solution to escape

from the local minimum effectively. To make the algorithm more competitive in

terms of the computing time, a simple and flexible data structure and a neighbourhood

reduction scheme are embedded. Finally, we adapt a new local search move

and an effective removal strategy for the LNS. The proposed AVNS was tested

on the benchmark data sets from the literature and produced very competitive

results.