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

Luca Talarico, Kenneth Sörensen and Johan Springael

Working Papers from University of Antwerp, Faculty of Business and Economics

Abstract: 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 instead of the vehicle capacity which is typical of capacitated vehicle routing problems. The risk of being robbed is assumed to be proportional both to the amount of cash being transported and the time/distance covered by the vehicle carrying the cash. The maximum vehicle exposure to risk limited by a certain risk threshold. A new metaheuristic, called aLNS (Ant colony heuristic with Large Neighbourhood Search), is described. The aLNS metaheuristic combines the ant colony heuristic for the travelling salesman problem and a large neighbourhood search heuristic within an iterated local search heuristic framework. A new library of rctvrp instances with known optimal solutions is proposed, and split in two sets named set O and set S respectively. The aLNS algorithm is extensively tested on small, medium and large benchmark instances and compared with all existing solution approaches for the rctvrp problem.

Keywords: Vehicle routing; Risk; Security; Cash-in-transit; Metaheuristic (search for similar items in EconPapers)
Pages: 22 pages
Date: 2014-10
New Economics Papers: this item is included in nep-cmp, nep-rmg and nep-tre
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Persistent link: https://EconPapers.repec.org/RePEc:ant:wpaper:2014024

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