Combating lead-time uncertainty in global supply chain's shipment-assignment: Is it wise to be risk-averse?

Abstract

In global supply chains, high uncertainty coming from liner shipping forces manufacturers who commit to on-time delivery to face great losses from tardiness or earliness. To find a reliable operational solution for shipment assignment, realizing the trade-off between the operations cost and reliability is highly essential. In this paper, a risk-hedging policy for shipment assignment is proposed. We incorporate risk aversion into the stochastic optimization model where the objective is to minimize the total deterministic operations cost and the weighted value-at-risk. The closed-form expressions of value-at-risk are derived and some structural properties of the optimization problem are revealed. Linearization techniques are utilized to make the proposed model tractable and solvable by an exact algorithm. Our computational studies further demonstrate the cost efficiency on systems reliability improvement through the risk hedging approach with job combination. It is interesting to uncover that being moderately risk-averse is wise, but possessing a very high risk-averse attitude is doing more harm than good as the increase of deterministic operations cost is much more significant than the decrease of value-at-risk. Being risk neutral may also be unwise as the chance of achieving the optimal expected total cost may be very low. In the extended models, we relax the assumptions and further consider scenarios with correlated shipping lead-times and stochastic exchange rate.