Optimal resource allocation in industrial complexes by distributed optimization and dynamic pricing

We address the distributed hierarchical optimization of industrial production complexes where the individual plants exchange resources via networks. Due to the site-wide couplings a centralized or a distributed hierarchical optimization is needed to achieve the best overall performance of the site and to balance the networks of the shared resources. We discuss market-like algorithms that set prices of the shared resources in order to influence the individual optimizers so that the overall operation converges to the site-wide optimum. A novel algorithm for price adjustment based on the quadratic approximation of the responses of the individual optimizers is presented. It shows convergence to the site-wide optimum with significantly less iterations in comparison to the standard subgradient-based method for a set of case studies, including a petrochemical complex.