An adaptive large-neighborhood search heuristic for a multi-period vehicle routing problem

- We design an ALNS based metaheuristic for the MPVRPSF.
- Our ALNS includes a set of novel algorithmic features and new operators.
- We compute a series of lower/upper bounds to evaluate the quality of the solution.
- We analyze the method in terms of computational time and solution quality.
- We study the contribution of different algorithmic components of our approach.

This problem involves optimizing product collection and redistribution from production locations to a set of processing plants over a planning horizon. This horizon consists of several days, and the collection-redistribution is performed on a repeating daily basis. A single routing plan must be prepared for the whole horizon, taking into account the seasonal variations in the supply. We model the problem using a sequence of periods, each corresponding to a season. We propose an adaptive large-neighborhood search with several specifically designed operators and features. The results show the excellent performance of the algorithm in terms of solution quality and computational efficiency.