Join order optimization is among the most crucial query optimization problems, and its central position is also evident in the new research field where quantum computing is applied to database ...

College of Mathematics and Information Science, Guangxi University, Nanning, China. School of Mathematical Science, Guangxi Teachers Education University, Nanning, China.. It is well known that the ...

Abstract: This paper presents a new two-stage multi-swarm particle swarm optimizer (TMPSO), which employs the multi-swarm method and takes two-stage different search strategies in the whole iteration ...

1 Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia 2 School of Quantitative Sciences, Institute of Strategic Industrial Decision ...

Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

In this project, I implemented Gradient Descent, Newton, Modified Newton, DFP and BFGS numerical optimization algorithms in C programming language. All of these algorithms are boosted with Armijo step ...

Abstract: The quasi-Newton methods is an effective and interesting methods and their good accuracy for unconstrained optimization. In this paper, a novel quasi-Newton equation is given based on the ...

This paper presents a numerical comparison between algorithms for unconstrained optimization that take account of sparsity in the second derivative matrix of the objective function. Some of the ...

ABSTRACT: Any attempts to apply techniques that are based on indirect measurements of parameters that are believed to correlate to any material properties (or state) in an in-line situation must by ...

To understand what exactly a convex function looks like refer to my notes at the following link :- https://drive.google.com/drive/folders/1cvmy0PdoP3-5sBN_LfmJ_KA ...