工业用水和水处理网络全局优化的强 P 公式

IF 1.8 3区 数学 Q1 Mathematics Journal of Global Optimization Pub Date : 2024-01-25 DOI:10.1007/s10898-023-01363-z
Xin Cheng, Xiang Li
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引用次数: 0

摘要

在工业用水和水处理网络中寻找最优流量分配的问题可以表述为非凸非线性程序或非凸混合整数非线性程序。非凸程序的全局优化效率在很大程度上取决于问题表述的强度。本文针对包括用水单位和水处理单位的水处理网络(WTN)和总水网络(TWN),提出了一种常用 P 公式的变体,称为 P (^*\)公式。对于这两类网络,我们都证明了在温和的约束一致性条件下,P(^*\)公式至少和 P 公式一样强。我们还证明,对于这两类网络,在某些约束一致性条件下,P(^*\)公式至少与基于分割分数的公式(称为 SF 公式)一样强。计算研究表明,P(^*\)公式明显优于P公式和SF公式。对于某些问题实例,P(^*\)公式比其他两种公式快几个数量级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A strong P-formulation for global optimization of industrial water-using and treatment networks

The problem of finding the optimal flow allocation within an industrial water-using and treatment network can be formulated into nonconvex nonlinear program or nonconvex mixed-integer nonlinear program. The efficiency of global optimization of the nonconvex program relies heavily on the strength of the problem formulation. In this paper, we propose a variant of the commonly used P-formulation, called the P\(^*\)-formulation, for the water treatment network (WTN) and the total water network (TWN) that includes water-using and water treatment units. For either type of networks, we prove that the P\(^*\)-formulation is at least as strong as the P-formulation under mild bound consistency conditions. We also prove for either type of networks that the P\(^*\)-formulation is at least as strong as the split-fraction based formulation (called SF-formulation) under certain bound consistency conditions. The computational study shows that the P\(^*\)-formulation significantly outperforms the P- and the SF-formulations. For some problem instances, the P\(^*\)-formulation is faster than the other two formulations by several orders of magnitudes.

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来源期刊
Journal of Global Optimization
Journal of Global Optimization 数学-应用数学
CiteScore
0.10
自引率
5.60%
发文量
137
审稿时长
6 months
期刊介绍: The Journal of Global Optimization publishes carefully refereed papers that encompass theoretical, computational, and applied aspects of global optimization. While the focus is on original research contributions dealing with the search for global optima of non-convex, multi-extremal problems, the journal’s scope covers optimization in the widest sense, including nonlinear, mixed integer, combinatorial, stochastic, robust, multi-objective optimization, computational geometry, and equilibrium problems. Relevant works on data-driven methods and optimization-based data mining are of special interest. In addition to papers covering theory and algorithms of global optimization, the journal publishes significant papers on numerical experiments, new testbeds, and applications in engineering, management, and the sciences. Applications of particular interest include healthcare, computational biochemistry, energy systems, telecommunications, and finance. Apart from full-length articles, the journal features short communications on both open and solved global optimization problems. It also offers reviews of relevant books and publishes special issues.
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