确定性MINLP优化的趋势和前景,用于化学过程的综合规划,调度,控制和设计
David A Liñán1, Luis A Ricardez-Sandoval1
1Department of Chemical Engineering, University of Waterloo, 200 University Ave W, Waterloo, ON, Canada.
混合整数非线性编程 (MINLP) 对于化学工程的综合决策至关重要. 对于工业4.0来说,MINLP算法的进步是必不可少的,它可以实现高效的过程设计,控制和操作.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 优化理论 优化理论
- 运营研究 运营研究
背景情况:
- 混合整数非线性编程 (MINLP) 最初涉及过程合成和设计.
- 由于行业的挑战,如可持续性和市场波动,MINLP的应用已经扩大到包括控制和运营决策.
- 现代工艺工厂正在采用自动化解决方案来进行综合决策,以提高利,资源效率和可持续性.
研究的目的:
- 探索化学工程的综合决策框架的研究机会和最近的进展.
- 为新兴的决定性MINLP优化算法提供了同时决策的概述.
- 讨论当前MINLP工具的功能和局限性,并建议结合新的优化理论.
主要方法:
- 审查和分析最先进的MINLP优化算法.
- 探索用于综合决策的决定性MINLP方法.
- 讨论将新的优化理论集成到MINLP框架中.
主要成果:
- 确定综合决策框架的关键研究方向.
- 新兴的确定性MINLP算法的概述,适用于同时做流程决策.
- 分析当前MINLP优化工具的多功能性和局限性.
结论:
- 可靠,高效和强大的MINLP算法对于化学工程中的工业4.0集成至关重要.
- 需要进一步开发MINLP框架,以处理复杂的同时决策问题.
- 结合新的优化理论可以增强MINLP功能,以实现先进的流程集成.
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