Optimize One Max Problem by PSO and CSA

Title

Optimize One Max Problem by PSO and CSA

Abstract

The optimal solution in mathematical concepts, computer science, and finance is to find the best solution out of all possible solutions. The type of optimization problem is determined by whether the variables are continuous or discrete.This study presents a One Max solution that shifts from the notion of optimization to the notion of the optimal strategy. Based on the time dimension difference, the CSA and PSO algorithms have been proposed as more effective in optimization, since the PSO algorithm is the oldest in the optimization field and CSA is modern. Nevertheless, despite being newly configured, the CSA algorithm has proven its effectiveness. Both algorithms must use values that are generated at random. Each cycle has a predetermined range of values for 100, 500, and 1000 cycles, and the values are calculated using the Sigmoid function. They go through 30 cycles with a number of function evaluations of 100,000. The Sigmoid function, which raises values above 0.5–1, is used to display the results for each range of 30 values. The results showed that the CSA algorithm outperformed PSO by 20% in terms of improvement values for each cycle (100, 500, and 1000). The CSA algorithm was selected as the preferred method for improving the One Max problem because of its efficiency and speed. Moreover, it has less dispersion than the PSO algorithm.

Scientific Type

تطبيقي

Link

https://link.springer.com/chapter/10.1007/978-981-99-3243-6_66

Journal volume

ICICT 2023 ,vol.1

Collaboration type

مشترك

Publish Date

July 25, 2023

Participated Universities (Publication)

Alnoor University

Al Kitab University

Scopus status

In Scopus

Scopus index year

2 023

Scopus quarter

4

Scopus citation score

0.699999988

Clarivate status

Not In Clarivate

Pub. Med. status

Not In PubMed

Author (Publication)

محمد ياسين عبدالله عبدالرحمن

Journal (Publication)

Lecture Notes in Networks and Systems

Publisher (Publication)

springer link

ISSN

2367-3370

Country (Publication)

United kingdom

Country type

عالمية

College (Publication)

College of Health and Medical Technologies

Departement (Publication)

Department of Anesthesia Techniques