화학공학소재연구정보센터
SIAM Journal on Control and Optimization, Vol.55, No.5, 3154-3170, 2017
RELAXATION AND PURIFICATION FOR NONCONVEX VARIATIONAL PROBLEMS IN DUAL BANACH SPACES: THE MINIMIZATION PRINCIPLE IN SATURATED MEASURE SPACES
We formulate bang-bang, purification, and 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 an 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.