(273d) Strategic Planning of Supply Chains Considering Extreme Events: Novel Heuristic and Application to the Petrochemical Industry
Applying stochastic programming to handle these uncertainties can quickly lead to prohibitively large models that cannot be solved in reasonable time. To remedy this, we propose a new methodology which combines the sample average approximation method with a selection heuristic for extreme event scenarios. Combined with multiobjective optimisation, this allows for the efficient analysis of the tradeoff between economic performance and disruption risk.
We demonstrate the effectiveness of this methodology in multiple case studies, achieving good solutions in reduced CPU time.