MODELLING INVESTMENTS ALLOCATION IN SUPPLY CHAIN RESILIENCE IMPROVEMENT

The concept of resilience is well developed as it has been studied extensively in last decade. The effort has been made to find ways to increase the supply chain resilience and thus to reduce an impact on supply chain long term performance. Supply chains and its management is a subject to globalization, which causes that suppliers, together with manufacturers and other shareholders of supply chains are getting more aware of the need to cooperate and find solutions to improve properties of all links to ensure proper long term functioning of supply chain and thus the prosperity of all links involved. There are still issues comprising how to build the overall supply chain resilience and how to support decisions regarding investments in the supply chain links to improve its properties and thus to increase its resilience. This article presents an initial experimental modelling of the impacts of investment on time to recovery after disruptions. The modelling approach assume that a mean time to recovery of specific links of supply chain can be reduced using investments to improve links properties and skills and availability of the supply chain is used as an indicator of resilience improvement. Modified transfer system model was used to model a studied system and Python 2.7.1 software with modules NUMPY and SCIPY was used to optimize the model using the SLSQP algorithm.