Optimising the sourcing strategy of a grain importing company, given uncertain backhaul availability

Abstract

The current sourcing strategy of a company which relies on the backhauls of third party logistic providers for transportation currently does not take the availability of backhauls into account. Therefore, there is uncertainty in the number of trucks that are available for transporting freight from a supplier to a customer. This uncertainty can lead to under deliveries of customer demand, and purchased product which cannot be picked up, which is undesirable. The problem is modelled as an extension of the Transportation Problem, adding product, time and size dimensions. The risks of unavailable backhauls in the sourcing strategy are modelled as expected penalties which are subtracted from the expected profit. A mixed integer linear program is developed to optimise the sourcing strategy. This program produces a truck schedule with corresponding contracts to buy at the suppliers. The real life instances that need to be solved on a daily basis, yield (tens of) millions of variables to optimize. As the solution is needed within an hour, using a global approach to obtain an exact solution is undesirable, due to the computing time needed. Therefore, a simulated annealing method is developed. The results of both these methods are analysed in terms of objective function value and computing time. It is recommended that the company implements exact solution method with a limited run time.