HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space

Mousavirad, S. J.Hakim Sabzevari University, Computer Engineering Department, Sabzevar, Iran (författare)

HMS-OS : Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space

Conference code: 176593; Cited By :1; Export Date: 8 June 2022; Conference Paper; Funding text 1: This research is funded within the SFEDU development program (PRIORITY 2030).
The human mental search (HMS) algorithm is a relatively recent population-based metaheuristic algorithm, which has shown competitive performance in solving complex optimisation problems. It is based on three main operators: mental search, grouping, and movement. In the original HMS algorithm, a clustering algorithm is used to group the current population in order to identify a promising region in search space, while candidate solutions then move towards the best candidate solution in the promising region. In this paper, we propose a novel HMS algorithm, HMS-OS, which is based on clustering in both objective and search space, where clustering in objective space finds a set of best candidate solutions whose centroid is then also used in updating the population. For further improvement, HMS-OS benefits from an adaptive selection of the number of mental processes in the mental search operator. Experimental results on CEC-2017 benchmark functions with dimensionalities of 50 and 100, and in comparison to other optimisation algorithms, indicate that HMS-OS yields excellent performance, superior to those of other methods.

TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik hsv//swe
ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering hsv//eng
Clustering
Human mental search
Metaheuristics
Objective space
Optimisation
Benchmarking
Clustering algorithms
Clusterings
Competitive performance
Complex optimization problems
Meta-heuristics algorithms
Metaheuristic
Optimisations
Search Algorithms
Search spaces
Optimization

Schaefer, G.Loughborough University, Department of Computer Science, Loughborough, United Kingdom (författare)
Korovin, I.Southern Federal University, Taganrog, Russian Federation (författare)
Oliva, D.Universidad de Guadalajara, Depto. de Ciencias Computacionales, Guadalajara, Mexico (författare)
Helali Moghadam, MahshidMälardalens universitet,RISE Research Institutes of Sweden, Sweden(Swepub:mdh)mhi05 (författare)
Saadatmand, Mehrdad,1980-RISE Research Institutes of Sweden(Swepub:mdh)msd03 (författare)
Hakim Sabzevari University, Computer Engineering Department, Sabzevar, IranLoughborough University, Department of Computer Science, Loughborough, United Kingdom (creator_code:org_t)

Ingår i:2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings: Institute of Electrical and Electronics Engineers Inc.9781728190488

Av författaren/redakt...: Mousavirad, S. J ...; Schaefer, G.; Korovin, I.; Oliva, D.; Helali Moghadam, ...; Saadatmand, Mehr ...

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