
Since the monotonicity of the best approximant is crucial to establish partial ordering methods, in this paper, we, respectively, characterize the best approximants in Banach function spaces and Lorentz spaces Γp,w, in which we especially focus on the monotonicity characterizations. We first study monotonicity characterizations of the metric projection operator onto sublattices in general Banach function spaces by the property Hg. The sufficient and necessary conditions for monotonicity of the metric projection onto cones and sublattices are then, respectively, established in Γp,w. The Lorentz spaces Γp,w are also shown to be reflexive under the condition RBp, which is the basis for the existence of the best approximant. As applications, by establishing the partial ordering methods based on the obtained monotonicity characterizations, the solvability and approximation theorems for best proximity points are deduced without imposing any contractive and compact conditions in Γp,w. Our results extend and improve many previous results in the field of the approximation and partial ordering theory.
monotone, Lorentz space, Banach function space, metric projection, best approximation
monotone, Lorentz space, Banach function space, metric projection, best approximation
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