Generalized Disjunctive Programming for Synthesis of Rice Drying Processes

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• 作者：Abdunnaser Younes ; Wongphaka Wongrat ; Ali Elkamel ; Peter L. Douglas ; Ali Lohi
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2010
• 出版时间：March 3, 2010
• 年：2010
• 卷：49
• 期：5
• 页码：2312-2325
• 全文大小：585K
• 年卷期：v.49,no.5(March 3, 2010)
• ISSN：1520-5045

文摘

Rice drying synthesis is an essential operation that has to be done carefully and cost-effectively. Fast drying can cause fissuring, which lowers the market value of the rice grains. Multipass drying systems are therefore used to bring the moisture content to desired levels gradually. To determine the best configuration of units and their corresponding operating conditions that maximize rice quality and minimize energy consumption, empirical models are used. However, empirical models have limited ranges of validity. Moreover, different mathematical models are possible for the same synthesis problem. This paper proposes a generalized disjunctive programming (GDP) framework for the synthesis problem of rice drying in order to increase the overall range of applicability of the empirical models and establish a consistent solution strategy. The proposed framework is investigated and tested on several case studies. Different drying strategies resulted from solving the synthesis problem with different empirical models, providing us with a broader vision of the mechanism of rice drying processes. The results indicate that the GDP framework can facilitate the modeling of the synthesis problem and increase the efficiency of optimization algorithms.