A multiscale decomposition method for the optimal planning and scheduling of multi-site continuous multiproduct plants
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This paper addresses the solution of simultaneous scheduling and planning problems in a production–distribution network of continuous multiproduct plants that involves different temporal and spatial scales. Production planning results in medium and long-term decisions, whereas production scheduling determines the timing and sequence of operations in the short-term. The production–distribution network is made up of several production sites distributing to different markets. The planning and scheduling model has to include spatial scales that go from a single production unit within a site, to a geographically distributed network. We propose to use two decomposition methods to solve this type of problems. One method corresponds to the extension of the bi-level decomposition of Erdirik-Dogan and Grossmann (2008) to multi-site, multi-market networks. A second method is a novel hybrid decomposition method that combines bi-level and spatial Lagrangean decomposition methods. We present four case studies to study the performance of the full space planning and scheduling model, the bi-level decomposition, and the bi-level Lagrangean method in profit maximization problems. Numerical results indicate that in large-scale problems, decomposition methods outperform the full space solution and that as problem size increases the hybrid decomposition method becomes faster than the bi-level decomposition alone.