Mathematical model of the metal mould surface temperature optimization

Mlýnek, Jaroslav; Knobloch, Roman; Srb, Radek

doi:10.1063/1.4936696

Search citation statements

Order By: Relevance

Paper Sections

Select...

A Real Optimization Task1

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2016

2020

Publication Types

Select...

Other3

Article2

Relationship

Self Cite2

Independent3

Authors

Journals

Cited by 5 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The aim of optimization is to locate a set of infrared heaters above a relatively complicated shell metal mould, so that the generated heat radiation intensity incident onto the mould surface is as uniform as possible. For the detailed description of this problem see the references [2] and [3]. Here we present only the results of CDEA and MDEA and their comparison regarding the attained minimum of the cost function.…”

Section: A Real Optimization Taskmentioning

confidence: 99%

The classic differential evolution algorithm and its convergence properties

2017

Self Cite

View full text Add to dashboard Cite

show abstract

Section: A Real Optimization Taskmentioning

confidence: 99%

The classic differential evolution algorithm and its convergence properties

2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…This task is described and solved in full detail in the article [3]. Further diverse and many-sided examples can be found in the book [5].…”

Section: Introductionmentioning

confidence: 99%

Convergence rate of the modified differential evolution algorithm

Knobloch

Mlýnek

Srb³

2017

AIP Conference Proceedings

Self Cite

View full text Add to dashboard Cite

Abstract. Differential evolution algorithms represent an efficient framework to solve complicated optimization tasks with many variables and complex constraints. Nevertheless, the classic differential evolution algorithm does not guarantee the convergence to the global minimum of the cost function. Therefore, the authors developed a modification of this algorithm that ensures asymptotic global convergence. The article provides a comparison of the ability to identify the global minimum of the cost function for the following three algorithms: the classic differential evolution algorithm, the above mentioned modified differential evolution algorithm and an algorithm of random sampling enhanced by a hill climbing procedure. We designed a series of numerical experiments to perform this comparison. The results indicate that the classic differential evolution algorithm is in general an extremely poor global optimizer (global minimum found in 2% of cases). On the other hand the performance of the modified differential evolution algorithm was considerably better (global minimum found in 83% of cases).

show abstract

An effect of mold surface temperature on final product properties in the injection molding of high-density polyethylene materials

Karagöz

2020

Polym. Bull.

View full text Add to dashboard Cite

Mathematical model of the metal mould surface temperature optimization

Cited by 5 publications

References 3 publications

The classic differential evolution algorithm and its convergence properties

The classic differential evolution algorithm and its convergence properties

Convergence rate of the modified differential evolution algorithm

An effect of mold surface temperature on final product properties in the injection molding of high-density polyethylene materials

Contact Info

Product

Resources

About