Optimization problems concern exploration of ... unique single-valued aggregated objective for unique combinations of the multiple objectives. The effectiveness of the pairing function based ...

So the extraction of more discriminative feature is the core of the task. In this paper, a joint optimization of multi-loss function for deep neural network is designed for this task with an aim to ...

The project is spreaded across 3 phases. Phase1:Extreme Point Calculation of a function Phase2:Optimization of Multivariable Function Phase3:Optimization of Constraint Objective function By Steepest ...

This paper embarks on a rigorous and comprehensive exploration of widely adopted optimization techniques, specifically focusing on their performance when applied to the notoriously challenging ...

This package offers an interface for objective functions in the context of (multi-objective) global optimization. It conveniently builds up on the S3 objects, i. e., an objective function is a S3 ...

However, many problems include multiple local minimizers ... Although the filled function method is an efficient global optimization method and different filled functions have been proposed, there are ...

Abstract: Real-time robust optimization of unknown expensive functions has been a challenging problem for data-driven based control applications. Most of the model-free control applications use ...