A surrogate-based multi-objective optimization framework is employed in the design of natural gas liquefaction processes using reliable, black-box process simulation. The conflicting objectives are minimizing both power consumption and heat exchanger area utilization. Pareto solutions single-mixed refrigerant (SMR) propane-precooled mixed (C3MR) compared to determine suitability each terms ener...

The goal of this paper is to estimate sparse linear regression models, where for a given partition G of input variables, the selected variables are chosen from a diverse set of groups in G. We consider a novel class of nonconvex constraint functions, and develop RepLasso, a greedy homotopy method that exploits geometrical properties of the constraint functions to build a sequence of suitably ad...

In most machine learning applications, classification accuracy is not the primary metric of interest. Binary classifiers which face class imbalance are often evaluated by the Fβ score, area under the precision-recall curve, Precision at K, and more. The maximization of many of these metrics can be expressed as a constrained optimization problem, where the constraint is a function of the classif...

Expensive computer simulations pose interesting challenges in design optimization. Conservation of function evaluations and the ability to deal with noisy responses become prime concerns. A common approach is to create an inexpensive approximation that may also smooth out some of the small scale noise. Typically, an approximation is made for the objective function and each of the constraint fun...

This article is the second part of a two-part survey series on large-scale global optimization. The first covered two major algorithmic approaches to optimization, namely, decomposition methods and hybridization methods, such as memetic algorithms local search. In this part, we focus sampling variation operators, approximation surrogate modeling, initialization parallelization. We also cover ra...

the realization optimality theory is a recent development in the original optimality theory which is proposed to deal with morphological issues especially the inflectional ones. its main idea is to consider the morphological realization rules as ranked violable language-specific constraints that control the realization processes and provide phonological information of grammatical morphemes. thi...

this study set out to investigate the distribution of the syntactic properties associatedwith the prodrop parameter by persian-speaking l2 learners of english in an attemptto examine the (un)attainability of native-like knowledge and (in)accessibility of ugin adult sla. to do so, 92 participants were assigned into different levels of l2knowledge based on their performances on the oxford placeme...

A ventricular pump is a device used to treat patients with heart failure. In this device, the blood pressure very important. On other hand, power use and efficiency are important due battery volume reduction. study, it was attempted introduce an optimum example of using computational fluid dynamics (CFD) as accurate method along kriging surrogate meta-models reduce time particle swarm optimizat...

Surrogate-based-optimization methods provide a means to minimize expensive highfidelity models at reduced computational cost. The methods are useful in problems for which two models of the same physical system exist: a high-fidelity model which is accurate and expensive, and a low-fidelity model which is less costly but less accurate. A number of model management techniques have been developed ...