Abstract
Abstract 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.
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