A computational framework for integrating campaign scheduling, dynamic optimization and optimal control in multi-unit batch processes
Autor: | Daniel Casas-Orozco, Gintaras V. Reklaitis, Francesco Rossi, Guido Buzzi-Ferraris, Flavio Manenti |
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Jazyk: | angličtina |
Rok vydání: | 2016 |
Předmět: |
Mathematical optimization
Optimization problem Job shop scheduling Computer science General Chemical Engineering Scheduling (production processes) 02 engineering and technology Dynamic priority scheduling 010402 general chemistry Optimal control 01 natural sciences 0104 chemical sciences Computer Science Applications Model predictive control 020401 chemical engineering Batch processing Multi unit 0204 chemical engineering |
Popis: | This contribution presents a framework for addressing the campaign scheduling, dynamic optimization and optimal control of batch processes in an integrated fashion. The strategy is comprised of an offline and an online phase. The first involves solving a conventional campaign scheduling problem and serves to generate key information needed in the second. The latter consists of a modified dynamic optimization/optimal control algorithm and serves to update the offline campaign schedule in real time as well as to provide the batch process with optimal control actions to achieve maximum campaign profit/performance. As a result of this two-phase architecture, the algorithm avoids the solution of a mixed-integer optimization problem online and can support virtually any process recipe structure including any type of recycle. To demonstrate its potential, we test the proposed methodology to solve the integrated campaign scheduling, dynamic optimization and optimal control of a batch plant for the production of nopol. |
Databáze: | OpenAIRE |
Externí odkaz: |
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