Recursive expected conditional value at risk in the fleet renewal problem with alternative fuel vehicles. (April 2016)

• Record Type: Journal Article
• Authors: Ansaripoor, Amir H.; Oliveira, Fernando S.; Liret, Anne
• Is Part Of: Transportation research. Volume 65(2016)
• Page Start: 156
• Page End: 171
• Publication Date: 2016-04
• Subjects: Risk management -- Fleet replacement -- Stochastic programming -- Conditional Value at Risk (CVaR); Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2015.12.010
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: A novel risk-based fleet management system is presented. We propose a recursive dynamic risk measure. We study how clustering affects risk management. A case study for a large UK based firm is investigated. Abstract: We study the fleet portfolio management problem faced by a firm deciding which alternative fuel vehicles (AFVs) to choose for its fleet to minimise the weighted average of cost and risk, in a stochastic multi-period setting. We consider different types of technology and vehicles with heterogeneous capabilities. We propose a new time consistent recursive risk measure, the Recursive Expected Conditional Value at Risk (RECVaR), which we prove to be coherent. We then solve the problem for a large UK based company, reporting how the optimal policies are affected by risk aversion and by the clustering for each type of vehicle.