(273d) Strategic Planning of Supply Chains Considering Extreme Events: Novel Heuristic and Application to the Petrochemical Industry

Chemical supply chains today are a crucial component in the ongoing supply of large population centres. However, episodes of extreme weather in particular have, in recent years, revealed vulnerabilities in global supply networks to high-impact events. And with a possible increase in both frequency and intensity of these events due to climate change, supply chains are at risk of disruption now more than ever, with potentially dire economic, societal, and environmental consequences.

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.