Hierarchically constrained blackbox optimization

Unconstrained and Constrained Blackbox Optimization: the Search Perspective

The SEARCH (Search Envisioned As Relation & Class Hierarchizing) framework developed elsewhere (Kargupta, 1995a; Kargupta & Goldberg, 1995) ooered an alternate perspective toward blackbox optimization (BBO)|optimization in presence of little domain knowledge. The SEARCH framework investigates the conditions essential for transcending the limits of random enumerative search using a framework dev...

Modeling an Augmented Lagrangian for Blackbox Constrained Optimization

Modeling an Augmented Lagrangian for Improved Blackbox Constrained Optimization

Constrained blackbox optimization is a difficult problem, with most approaches coming from the mathematical programming literature. The statistical literature is sparse, especially in addressing problems with nontrivial constraints. This situation is unfortunate because statistical methods have many attractive properties: global scope, handling noisy objectives, sensitivity analysis, and so for...

Snow water equivalent estimation using blackbox optimization

Accurate measurements of snow water equivalent (SWE) is an important factor in managing water resources for hydroelectric power generation. SWE over a catchment area may be estimated via kriging on measures obtained by snow monitoring devices positioned at strategic locations. The question studied in this paper is to find the device locations that minimize the kriging interpolation error of the...

SEARCH, Blackbox Optimization, And Sample Complexity

The SEARCH (Search Envisioned As Relation & Class Hierarchizing) framework developed elsewhere (Kargupta, 1995) ooered an alternate perspective toward blackbox optimization (BBO)|optimization in presence of little domain knowledge. The SEARCH framework investigated the conditions essential for transcending the limits of random enumerative search using a framework developed in terms of relations...