The Nonconvex Second-Order Cone: Algebraic Structure Toward Optimization

IF 1.6 3区 数学 Q2 MATHEMATICS, APPLIED
Baha Alzalg, Lilia Benakkouche
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Abstract

This paper explores the nonconvex second-order cone as a nonconvex conic extension of the known convex second-order cone in optimization, as well as a higher-dimensional conic extension of the known causality cone in relativity. The nonconvex second-order cone can be used to reformulate nonconvex quadratic programming and nonconvex quadratically constrained quadratic program in conic format. The cone can also arise in real-world applications, such as facility location problems in optimization when some existing facilities are more likely to be closer to new facilities than other existing facilities. We define notions of the algebraic structure of the nonconvex second-order cone and show that its ambient space is commutative and power-associative, wherein elements always have real eigenvalues; this is remarkable because it is not the case for arbitrary Jordan algebras. We will also find that the ambient space of this nonconvex cone is rank-independent of its dimension; this is also notable because it is not the case for algebras of arbitrary convex cones. What is more noteworthy is that we prove that the nonconvex second-order cone equals the cone of squares of its ambient space; this is not the case for all non-Euclidean Jordan algebras. Finally, numerous algebraic properties that already exist in the framework of the convex second-order cone are generalized to the framework of the nonconvex second-order cone.

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非凸二阶锥体:面向优化的代数结构
本文探讨的非凸二阶锥是优化中已知凸二阶锥的非凸圆锥扩展,也是相对论中已知因果关系锥的高维圆锥扩展。非凸二阶锥可用于以圆锥格式重新表述非凸二次方程程序和非凸二次约束二次方程程序。在现实世界的应用中,如优化中的设施选址问题,当一些现有设施比其他现有设施更有可能靠近新设施时,也会出现锥形。我们定义了非凸二阶圆锥的代数结构概念,并证明其周围空间是交换和幂相关的,其中的元素总是具有实特征值;这一点非常重要,因为对于任意的约旦代数来说,情况并非如此。我们还将发现,这种非凸锥的环境空间与维数无关;这一点也很重要,因为任意凸锥的代数方程并不如此。更值得注意的是,我们证明了非凸二阶锥等于其环境空间的方锥;而所有非欧几里得乔丹代数代数却并非如此。最后,我们将凸二阶锥框架中已有的许多代数性质推广到了非凸二阶锥框架中。
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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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
149
审稿时长
9.9 months
期刊介绍: The Journal of Optimization Theory and Applications is devoted to the publication of carefully selected regular papers, invited papers, survey papers, technical notes, book notices, and forums that cover mathematical optimization techniques and their applications to science and engineering. Typical theoretical areas include linear, nonlinear, mathematical, and dynamic programming. Among the areas of application covered are mathematical economics, mathematical physics and biology, and aerospace, chemical, civil, electrical, and mechanical engineering.
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