Abstract: This paper investigates the optimization of production process decisions based on nonlinear programming and particle swarm optimization genetic algorithm ...

Low-rank priors, a fundamental assumption for dimensionality reduction, have attracted a lot of attention in the last decade. They have wide applications in machine learning, data analysis, ...

Rapid urbanization and economic development have inevitably led to light pollution. However, currently the world has not yet formed a unified technical standard for light pollution, and light ...

This repository contains my solutions and notes for the NPTEL Programming, Data Structures And Algorithms Using Python course. The course covers fundamental, intermediate programming, data structures, ...

Abstract: A graph-structured nonlinear program (NLP) is a nonlinear optimization problem whose algebraic structure is induced by a graph. These problems arise in diverse applications such as dynamic ...

Algorithms and Data Structure are two of the most fundamentals and important topics from Computer Science which is used everywhere in software development. Algorithms and Data Structure are two of the ...

Real-world systems with complicated quality-of-service guarantees may require a delicate balance between throughput and latency in order to meet operating requirements in a cost-efficient manner. The ...

ABSTRACT: We present a new derivative-free optimization algorithm based on the sparse grid numerical integration. The algorithm applies to a smooth nonlinear objective function where calculating its ...