数学优化
双线性插值
变量(数学)
航程(航空)
线性化
整数(计算机科学)
二进制数
非线性系统
计算机科学
上下界
数学
物理
程序设计语言
材料科学
复合材料
数学分析
算术
量子力学
计算机视觉
作者
Yifu Chen,Christos T. Maravelias
出处
期刊:Informs Journal on Computing
日期:2022-02-15
卷期号:34 (4): 2073-2090
被引量:2
标识
DOI:10.1287/ijoc.2021.1140
摘要
Multiperiod blending has a number of important applications in a range of industrial sectors. It is typically formulated as a nonconvex mixed integer nonlinear program (MINLP), which involves binary variables and bilinear terms. In this study, we first propose a reformulation of the constraints involving bilinear terms using lifting. We introduce a method for calculating tight bounds on the lifted variables calculated by aggregating multiple constraints. We propose valid constraints derived from the reformulation-linearization technique (RLT) that use the bounds on the lifted variables to further tighten the formulation. Computational results indicate our method can substantially reduce the solution time and optimality gap. Summary of Contribution: In this paper, we study the multiperiod blending problem, which has a number of important applications in a range of industrial sectors, such as refining, chemical production, mining, and wastewater management. Solving this problem efficiently leads to significant economic and environmental benefits. However, solving even medium-scale instances to global optimality remains challenging. To address this challenge, we propose a variable bound tightening algorithm and tightening constraints for multiperiod blending. Computational results show that our methods can substantially reduce the solution time and optimality gap.
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