Title
An adaptive and diversified vehicle routing approach to reducing the security risk of cash-in-transit operations.
Abstract
We consider the route optimization problem of transporting valuables in cash-in-transit CIT operations. The problem arises as a rich variant of the capacitated vehicle routing problem CVRP with time windows and pickup and deliveries. Due to the high-risk nature of this operation e.g., robberies we consider a bi-objective function where we attempt to minimize the total transportation cost and the security risk of transporting valuables along the designed routes. For risk minimization, we propose a composite risk measure that is a weighted sum of two risk components: i following the same or very similar routes, and ii visiting neighborhoods with low socio-economic status along the routes. We also consider vehicle capacities in terms of monetary value carried as per insurance regulations. We develop an adaptive randomized bi-objective path selection algorithm that uses the composite risk measure in choosing alternative paths between origin-destination pairs over a sequence of days. We solve the rich CVRP approximately for each day with updated costs. We test our solution approach on a data set from a CIT delivery service provider and provide insights on how the routes diversify daily. Our approach generates a spectrum of solutions with cost-risk trade-off to support decision making. © 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 693, 256-269 2017
Year
DOI
Venue
2017
10.1002/net.21735
Networks
Keywords
Field
DocType
city logistics,cash-in-transit transportation,security risk,pickup and delivery with time windows,adaptive randomized algorithm
Mathematical optimization,Transportation cost,Vehicle routing problem,Selection algorithm,Service provider,Minification,Risk measure,Optimization problem,Mathematics,Cash
Journal
Volume
Issue
ISSN
69
3
0028-3045
Citations 
PageRank 
References 
2
0.37
15
Authors
3
Name
Order
Citations
PageRank
Burçin Bozkaya1244.71
F. Sibel Salman226925.92
Kaan Telciler320.37