What is the best supply chain algorithm

Innovative algorithms for supply chain optimization

The efficiency of distribution and production networks (supply chain networks) depends on many input variables. Along the value chain, these are performance parameters such as order quantities, production locations, transport routes and product ranges. So far there has been no solution that adequately takes into account all influencing factors and thus exploits the full potential of supply chain networks. The reasons are the high complexity of the structure and uncertainties in the input variables. Fluctuating input variables represent essential risk factors for a company and must be absorbed by high stocks. The growing complexity of value chains and increasing expectations of end customers make this topic more important and topical for companies than ever before.

The classic approach to optimizing distribution and production networks is based on deterministic models, i.e. fixed relationships between influencing variables and results, as well as best, worst and average-case scenarios. In this project, stochastic simulation and mathematical optimization are combined in order to take dynamic components into account with powerful network flow algorithms. The aim is to research and develop innovative and highly efficient methods, algorithms and procedures for network optimization with uncertain input variables.

The consideration of uncertain input variables is an important step for the user in order to use the optimization software realistically. While large value chains could previously only be mapped deterministically, the results of this project enable holistic optimization while taking real risks into account.