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Efficient optimization of a large-scale biorefinery system using a novel decomposition based approach
Chemical Engineering Research and Design ( IF 3.9 ) Pub Date : 2020-05-31 , DOI: 10.1016/j.cherd.2020.05.023
Varun Punnathanam , Yogendra Shastri

Biorefinery design problems that consider processing and supply chain together are generally large-scale mixed integer linear programs (MILP) that are computationally difficult to solve. This work considers one such large-scale problem and proposes a solution method to solve it efficiently. The proposed method utilizes the Dantzig-Wolfe decomposition framework and a novel heuristic to simplify the original problem. This simplification is done using the sub-problem solutions obtained within the Dantzig-Wolfe decomposition iterations. The resulting simplified problem can be easily solved using standard procedures to obtain the final solution for the original problem. The proposed method is observed to be up to 92% faster than the standard CPLEX® MILP solver and can solve large-scale problems which are not solvable using standard approaches. A large-scale biorefinery design problem for the production of ethanol from lignocellulosic biomass in Maharashtra, India is solved. For an ethanol demand of 20 million kg/month, the minimum ethanol cost was determined to be INR 47.4 per litre. This method enables the formulation of more comprehensive biorefinery design models and can be employed on similarly structured large MILP problems in other fields.



中文翻译:

使用基于分解的新方法对大型生物精炼系统进行有效的优化

同时考虑加工和供应链的生物炼油厂设计问题通常是大型混合整数线性程序(MILP),在计算上难以解决。这项工作考虑了这样一个大问题,并提出了一种有效解决问题的解决方法。所提出的方法利用了Dantzig-Wolfe分解框架和一种新颖的启发式方法来简化原始问题。使用在Dantzig-Wolfe分解迭代中获得的子问题解决方案来完成此简化。使用标准程序可以轻松解决由此产生的简化问题,从而获得原始问题的最终解决方案。据观察,所提出的方法比标准CPLEX®MILP求解器快92%,并且可以解决使用标准方法无法解决的大规模问题。解决了印度马哈拉施特拉邦从木质纤维素生物质生产乙醇的大规模生物精炼厂设计问题。对于2000万公斤/月的乙醇需求,确定的最低乙醇成本为每升47.4印度卢比。这种方法可以制定更全面的生物炼油厂设计模型,并且可以用于其他领域中类似结构的大型MILP问题。

更新日期:2020-05-31
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