A hybrid primal-dual-PSO (pdipmPSO) algorithm for swarm robotics flocking strategy

Emmanuel Gbenga Dada; E. Ramlan

doi:10.1109/ICCTIM.2015.7224599

A hybrid primal-dual-PSO (pdipmPSO) algorithm for swarm robotics flocking strategy

Emmanuel Gbenga Dada, E. Ramlan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

This paper presents a hybrid algorithm called Primal-Dual-PSO algorithm to address the problem of swarm robotics flocking motion. This algorithm combines the explorative ability of PSO with the exploitative capacity of the Primal Dual Interior Point Method. We hypothesize that the fusion of the two algorithms provides a strong probability of avoiding premature convergence, and also ensure that the robots are not trapped in their local minimal. Our simulation result provides a clear indication of the effectiveness of the algorithm. The hybrid algorithm performs better in terms of precision, rate of convergence, steadiness, robustness and flocking capability for homogenous set of swarm robots.

Original language	English
Title of host publication	2015 2nd International Conference on Computing Technology and Information Management, ICCTIM 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	93-98
Number of pages	6
ISBN (Electronic)	9781479962112
DOIs	https://doi.org/10.1109/ICCTIM.2015.7224599
Publication status	Published (in print/issue) - 25 Aug 2015
Event	2nd International Conference on Computing Technology and Information Management, ICCTIM 2015 - Johor, Malaysia Duration: 21 Apr 2015 → 23 Apr 2015

Conference

Conference	2nd International Conference on Computing Technology and Information Management, ICCTIM 2015
Country/Territory	Malaysia
City	Johor
Period	21/04/15 → 23/04/15

Keywords

gbest
Interior Point Method
lbest
Particle Swarm Optimization (PSO)
Primal-Dual

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10.1109/ICCTIM.2015.7224599

Cite this

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title = "A hybrid primal-dual-PSO (pdipmPSO) algorithm for swarm robotics flocking strategy",

abstract = "This paper presents a hybrid algorithm called Primal-Dual-PSO algorithm to address the problem of swarm robotics flocking motion. This algorithm combines the explorative ability of PSO with the exploitative capacity of the Primal Dual Interior Point Method. We hypothesize that the fusion of the two algorithms provides a strong probability of avoiding premature convergence, and also ensure that the robots are not trapped in their local minimal. Our simulation result provides a clear indication of the effectiveness of the algorithm. The hybrid algorithm performs better in terms of precision, rate of convergence, steadiness, robustness and flocking capability for homogenous set of swarm robots.",

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author = "Dada, {Emmanuel Gbenga} and E. Ramlan",

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doi = "10.1109/ICCTIM.2015.7224599",

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Dada, EG & Ramlan, E 2015, A hybrid primal-dual-PSO (pdipmPSO) algorithm for swarm robotics flocking strategy. in 2015 2nd International Conference on Computing Technology and Information Management, ICCTIM 2015., 7224599, Institute of Electrical and Electronics Engineers Inc., pp. 93-98, 2nd International Conference on Computing Technology and Information Management, ICCTIM 2015, Johor, Malaysia, 21/04/15. https://doi.org/10.1109/ICCTIM.2015.7224599

A hybrid primal-dual-PSO (pdipmPSO) algorithm for swarm robotics flocking strategy. / Dada, Emmanuel Gbenga; Ramlan, E.
2015 2nd International Conference on Computing Technology and Information Management, ICCTIM 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 93-98 7224599.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A hybrid primal-dual-PSO (pdipmPSO) algorithm for swarm robotics flocking strategy

AU - Dada, Emmanuel Gbenga

AU - Ramlan, E.

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N2 - This paper presents a hybrid algorithm called Primal-Dual-PSO algorithm to address the problem of swarm robotics flocking motion. This algorithm combines the explorative ability of PSO with the exploitative capacity of the Primal Dual Interior Point Method. We hypothesize that the fusion of the two algorithms provides a strong probability of avoiding premature convergence, and also ensure that the robots are not trapped in their local minimal. Our simulation result provides a clear indication of the effectiveness of the algorithm. The hybrid algorithm performs better in terms of precision, rate of convergence, steadiness, robustness and flocking capability for homogenous set of swarm robots.

AB - This paper presents a hybrid algorithm called Primal-Dual-PSO algorithm to address the problem of swarm robotics flocking motion. This algorithm combines the explorative ability of PSO with the exploitative capacity of the Primal Dual Interior Point Method. We hypothesize that the fusion of the two algorithms provides a strong probability of avoiding premature convergence, and also ensure that the robots are not trapped in their local minimal. Our simulation result provides a clear indication of the effectiveness of the algorithm. The hybrid algorithm performs better in terms of precision, rate of convergence, steadiness, robustness and flocking capability for homogenous set of swarm robots.

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KW - Interior Point Method

KW - lbest

KW - Particle Swarm Optimization (PSO)

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BT - 2015 2nd International Conference on Computing Technology and Information Management, ICCTIM 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd International Conference on Computing Technology and Information Management, ICCTIM 2015

Y2 - 21 April 2015 through 23 April 2015

ER -

A hybrid primal-dual-PSO (pdipmPSO) algorithm for swarm robotics flocking strategy

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Keywords

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