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Relaxation and Purification for Nonconvex Variational Problems in Dual Banach Spaces: The Minimization Principle in Saturated Measure Spaces

机译:对偶Banach空间中非凸变分问题的松弛和纯化:饱和测度空间中的最小化原理

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Abstract: We formulate bang-bang, purification, minimization principles in dual Banach spaces with Gelfand integrals and provide a complete characterization of the saturation property of finite measure spaces. We also present a new application of the relaxation technique to large economies with infinite-dimensional commodity spaces, where the space of agents is modeled as a finite measure space. We propose a “relaxation” of large economies, which is regarded as a reasonable convexification of original economies. Under the saturation hypothesis, the relaxation and purification techniques enable us to prove the existence of Pareto optimal allocations without convexity assumptions.
机译:摘要:我们在具有Gelfand积分的对偶Banach空间中制定了爆炸,纯化,最小化原理,并提供了对有限度量空间饱和特性的完整表征。我们还提出了松弛技术在具有无限维商品空间的大型经济体中的新应用,其中,代理商空间被建模为有限度量空间。我们提出了对大型经济体的“放松”,这被认为是原始经济体的合理凸现。在饱和假设下,松弛和提纯技术使我们能够证明没有凸性假设的帕累托最优分配的存在。

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