ISSN 2708-244X
 

Review Article 


Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods

Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac.

Abstract
The optimization process is concerned with the finding of the best solution from all possible solutions for a given problem. In this paper, the focus is on the importation step of HS algorithm using Scramble Mutation. The essential idea of new type of modification on variable. The selection method of Scramble mutation hybridized onto harmony search. The resulting variant of HS is called the Scramble Mutation Harmony Search algorithm (SMHS). For optimization problems to avoid premature convergence problem due by using one of the mutations to increase the number of solutions proposed, thus improving the performance of the Harmony Search (HS) algorithm, by maintaining diversity in the use of different rates to modify the proposed solutions. Compare the SMHS with HS and other existing methods to validate the efficiency of the SMHS. The results obtained by comparing the SMHS with basic HS and two other methods (i.e. MHS and DLHS), using ten benchmark functions illustrated that SMHS outperformed the basic HS for majority of the functions. It is therefore concluded that the SMHS algorithms is highly sensitive for the HMCR and obtains the best results at high value of HMCR. For harmony memory size, the HS performs better when HMS is relatively small. In the same vein, the SMHS performs better when the number of domain ( ) is compatible with HMS.

Key words: Optimizations, Evolutionary Algorithm (EA), Harmony Search (HS), Genetic Scramble Mutation Harmony Search (SMHS)


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Khamiss M. S. Ahmeda
Articles by Mahmmoud Alawanb
Articles by Fatima Mustafac
on Google
on Google Scholar

How to Cite this Article
Pubmed Style

Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac. Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods. AJAS. 2020; 1(1): 38-43.


Web Style

Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac. Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods. http://www.albahitjas.com/?mno=97427 [Access: July 22, 2020].


AMA (American Medical Association) Style

Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac. Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods. AJAS. 2020; 1(1): 38-43.



Vancouver/ICMJE Style

Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac. Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods. AJAS. (2020), [cited July 22, 2020]; 1(1): 38-43.



Harvard Style

Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac (2020) Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods. AJAS, 1 (1), 38-43.



Turabian Style

Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac. 2020. Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods. Albahit journal of applied sciences, 1 (1), 38-43.



Chicago Style

Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac. "Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods." Albahit journal of applied sciences 1 (2020), 38-43.



MLA (The Modern Language Association) Style

Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac. "Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods." Albahit journal of applied sciences 1.1 (2020), 38-43. Print.



APA (American Psychological Association) Style

Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac (2020) Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods. Albahit journal of applied sciences, 1 (1), 38-43.





Most Viewed Articles
  • Trends in Designing Databases for E-learning Systems
    Husam Ali Suleiman Khalifa
    AJAS. 2020; 1(1): 16-21
    » Abstract

  • Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods
    Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac
    AJAS. 2020; 1(1): 38-43
    » Abstract

  • Recycling Building Demolition Waste as an Asphalt Binder Course in Road Pavements: a Case Study in Benghazi
    Manal S Ali Abmdas S Ali Abmdas, Halima Saeid Omar Saeid
    AJAS. 2020; 1(1): 28-34
    » Abstract

  • Chemical specifications for raw materials used in the Kufa cement industry in Iraq
    Jameel Al-Naffakh, Mohammed Al-fahham, israa kadum
    AJAS. 2020; 1(1): 65-69
    » Abstract

  • Evaluation of Geostatistical Interpolation Methods For Rainfall data Estimation In Libya.
    Lubna soliman BenTaher
    AJAS. 2020; 1(1): 54-59
    » Abstract

  • Most Downloaded
  • Trends in Designing Databases for E-learning Systems
    Husam Ali Suleiman Khalifa
    AJAS. 2020; 1(1): 16-21
    » Abstract

  • Global Optimization of SMHS to Enhance The Performance of Diversity and Sensitivity via Comparing with HS and other Existing Methods
    Khamiss M. S. Ahmeda, Mahmmoud Alawanb, Fatima Mustafac
    AJAS. 2020; 1(1): 38-43
    » Abstract

  • Recycling Building Demolition Waste as an Asphalt Binder Course in Road Pavements: a Case Study in Benghazi
    Manal S Ali Abmdas S Ali Abmdas, Halima Saeid Omar Saeid
    AJAS. 2020; 1(1): 28-34
    » Abstract

  • Chemical specifications for raw materials used in the Kufa cement industry in Iraq
    Jameel Al-Naffakh, Mohammed Al-fahham, israa kadum
    AJAS. 2020; 1(1): 65-69
    » Abstract

  • Evaluation of Geostatistical Interpolation Methods For Rainfall data Estimation In Libya.
    Lubna soliman BenTaher
    AJAS. 2020; 1(1): 54-59
    » Abstract

  • Most Cited Articles