Chaotic Spiral Dynamics Optimization Algorithm

Hashim, Mohd Ruzaini; Tokhi, M. O.

doi:10.1142/9789813149137_0065

Cited by 3 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, two new phases, namely elimination and dispersal, are introduced. Similarly, Hashim et al have proposed the chaotic SDO algorithm logistic chaotic map patterns in the conventional SDO [26,27]. The chaotic map pattern helps in the initial population distribution rather than randomly in conventional SDO.…”

Section: Improved Versions Of Spiral Dynamics Optimization Algorithmmentioning

confidence: 99%

Recent Advances and Applications of Spiral Dynamics Optimization Algorithm: A Review

et al. 2022

View full text Add to dashboard Cite

This paper comprehensively reviews the spiral dynamics optimization (SDO) algorithm and investigates its characteristics. SDO algorithm is one of the most straightforward physics-based optimization algorithms and is successfully applied in various broad fields. This paper describes the recent advances of the SDO algorithm, including its adaptive, improved, and hybrid approaches. The growth of the SDO algorithm and its application in various areas, theoretical analysis, and comparison with its preceding and other algorithms are also described in detail. A detailed description of different spiral paths, their characteristics, and the application of these spiral approaches in developing and improving other optimization algorithms are comprehensively presented. The review concludes the current works on the SDO algorithm, highlighting its shortcomings and suggesting possible future research perspectives.

show abstract

Section: Improved Versions Of Spiral Dynamics Optimization Algorithmmentioning

confidence: 99%

Recent Advances and Applications of Spiral Dynamics Optimization Algorithm: A Review

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In recent years, several studies have addressed the SDA, including modifying its structure to improve it, hybridizing the SDA  ISSN: 2302-9285 with other algorithms to increase its efficiency, and applying it in engineering problems. These studies involved the modification of the SDA using a chaotic map [2], the hybridization of the SDA with the artificial bee colony (ABC) algorithm [3], and the application of the SDA to solve mixed-integer nonlinear programming problems [4]. The studies all demonstrated successful improvements to the SDA.…”

Section: Introductionmentioning

confidence: 99%

Super-opposition spiral dynamic-based fuzzy control for an inverted pendulum system

2022

View full text Add to dashboard Cite

This paper presents a hybrid spiral dynamic algorithm with a super-opposition spiral dynamic algorithm (SOSDA) strategy. An improvement on the spiral dynamic algorithm (SDA), this method uses a concept centered on opposition-based learning, which is used to evaluate the fitness of agents at the opposite location to the current solution. The SDA is a simple-structured and deterministic type of algorithm, which also performs competitively in terms of solution accuracy. However, its deterministic characteristic means the SDA suffers premature convergence caused by the unbalanced diversification and intensification during its search procedure. Thus, the algorithm fails to achieve highly accurate solutions. It is proposed that adopting super-opposition into the SDA would enable the deterministic and random techniques to complement one another. The SOSDA was tested on four benchmark functions and compared to the original SDA. To analyze the result statistically, the Friedman and Wilcoxon tests were conducted. Furthermore, the SOSDA was applied to optimize the parameters of an interval type-2 fuzzy logic control (IT2FLC) for an inverted pendulum (IP). The statistical results produced by the SOSDA for both benchmark functions and the IP show that the proposed algorithm significantly outperformed the SDA. The SOSDA-based IT2FLC scheme also produced better IP responses than the SDA-based IT2FLC.

show abstract

Solving microelectronic thermal management problems using a generalized spiral optimization algorithm

et al. 2021

View full text Add to dashboard Cite

Chaotic Spiral Dynamics Optimization Algorithm

Cited by 3 publications

References 3 publications

Recent Advances and Applications of Spiral Dynamics Optimization Algorithm: A Review

Recent Advances and Applications of Spiral Dynamics Optimization Algorithm: A Review

Super-opposition spiral dynamic-based fuzzy control for an inverted pendulum system

Solving microelectronic thermal management problems using a generalized spiral optimization algorithm

Contact Info

Product

Resources

About