A large neighbourhood metaheuristic for the risk-constrained cash-in-transit vehicle routing problem

In this paper, we propose a new metaheuristic to solve the Risk constrained Cash-in-Transit Vehicle Routing Problem (RCTVRP). The RCTVRP is a variant of the well-known capacitated vehicle routing problem and models the problem of routing vehicles in the cash-in-transit sector. In the RCTVRP, the risk associated with a robbery represents a critical aspect that is treated as a limiting factor subject to a maximum risk threshold. A new metaheuristic, called ACO-LNS is developed. It combines the ant colony heuristic for the travelling salesman problem and a variable neighbourhood descent within an large neighbourhood search framework. A new library of RCTVRP instances with known optimal solutions is proposed. The ACO-INS is extensively tested on small, medium and large benchmark instances and compared with all existing solution approaches for the RCTVRP. (C) 2016 Elsevier Ltd. All rights reserved.

Publication year:2017

Keywords:A1 Journal article

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BOF-publication weight:3

CSS-citation score:2

Authors:International

Authors from:Higher Education

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