NDLI: Examination of benefits of personal fitness improvement dependent inertia for Particle Swarm Optimization

Content Provider	Springer Nature Link
Author	Družeta, Siniša Ivić, Stefan
Copyright Year	2016
Abstract	Since its invention, Particle Swarm Optimization (PSO) has received significant attention in the optimization community, which spawned numerous PSO modifications, variations and applications. However, most of the PSO improvements come with impaired simplicity and increased computational cost of the method. As an effort to advance the PSO performance through enhanced particle awareness of its own fitness, a novel PSO modification based on personal fitness improvement dependent inertia (PFIDI) is proposed. The PFIDI technique used in the paper employs a straightforward and elegant switch-like condition on inertia which turns off a particle’s inertia when the particle stops advancing in a direction of better fitness. Considering the effects of this technique on the particle movement logic, the method is called “Languid PSO” (LPSO). So as to attain a reliable assessment of the effects of PFIDI as implemented in LPSO, a massive computing effort was exerted for the benchmark testing, in which LPSO accuracy was compared to standard PSO accuracy on 30 test functions (CEC 2014 test suite), three problem space dimensionalities (10, 20 and 50), and a wide range of PSO parameters. The results clearly show the advantages of PFIDI-enabled LPSO, which predominantly outperforms standard PSO, both across all parameter combinations and for best-achieving PSO parameters. The success of the proposed PSO modification, coupled with its elegance and computational simplicity (less than 1.1 % increase in computational cost over standard PSO), indicates that fitness-based inertia may represent a rewarding approach in the PSO research.
Starting Page	3387
Ending Page	3400
Page Count	14
File Format	PDF
ISSN	14327643
Journal	Soft Computing
Volume Number	21
Issue Number	12
e-ISSN	14337479
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-01-11
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Particle Swarm Optimization Inertia weight Fitness based inertia Swarm intelligence Computational Intelligence Artificial Intelligence (incl. Robotics) Mathematical Logic and Foundations Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Software Geometry and Topology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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