![]() ![]() A tailored generalized Benders decomposition (GBD) algorithm is applied to efficiently solve the resulting large nonconvex mixed-integer nonlinear program by exploring the particular model structure. ![]() The scheduling and operation layers are linked with the task history state variables in the state space RTN model. General complications in scheduling and control can be fully represented in this modeling framework, such as customer orders, transfer policies, and requirements on product quality and process safety. The process is described by the resource task network (RTN) representation coupled with detailed first-principles process dynamic models. The method introduces a discrete time formulation for simultaneous optimization of scheduling and operating decisions. We propose a model-based optimization approach for the integration of production scheduling and dynamic process operation for general continuous/batch processes. ![]()
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