Glowworm swarm optimization
Encyclopedia
The glowworm swarm optimization (GSO) is a swarm intelligence
optimization
algorithm
developed based on the behaviour of glowworm
s (also known as fireflies or lightning bugs). The behaviour pattern of glowworms which is used for this algorithm is the apparent capability of the glowworms to change the intensity of the luciferin emission and thus appear to glow at different intensities.
1.The GSO algorithm makes the agents glow at intensities approximately proportional to the function value being optimized. It is assumed that glowworms of brighter intensities attract glowworms that have lower intensity.
2.The second significant part of the algorithm incorporates a dynamic decision range by which the effect of distant glowworms are discounted when a glowworm has sufficient number of neighbours or the range goes beyond the range of perception of the glowworms.
The part 2 of the algorithm makes it different from Firefly algorithm
where there is no "sufficient number o neighbours" limit and there is no perception limit based on distance.
This two "cognitive limits" allows swarm
s of glowworms to split into sub-groups and converge to high function value points. This property of the algorithm allows it to be used to identify multiple peaks of a multi-modal function and makes it part of Evolutionary multi-modal optimization
algorithms family.
The GSO algorithm was developed and introduced by K.N. Krishnanand and D. Ghose in 2005 at the Guidance, Control, and Decision Systems Laboratory in the Department of Aerospace Engineering at the Indian Institute of Science
, Bangalore
, India
. Subsequently, it has been used in various applications and several papers have appeared in the literature using the GSO algorithm.
Swarm intelligence
Swarm intelligence is the collective behaviour of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence...
optimization
Optimization (mathematics)
In mathematics, computational science, or management science, mathematical optimization refers to the selection of a best element from some set of available alternatives....
algorithm
Algorithm
In mathematics and computer science, an algorithm is an effective method expressed as a finite list of well-defined instructions for calculating a function. Algorithms are used for calculation, data processing, and automated reasoning...
developed based on the behaviour of glowworm
Glowworm
Glowworm, or glow worm, is the common name for various groups of insect larvae and adult larviform females that glow through bioluminescence. They may sometimes resemble worms, but all are insects .-Classification:Major families are:* Lampyridae , found around the world...
s (also known as fireflies or lightning bugs). The behaviour pattern of glowworms which is used for this algorithm is the apparent capability of the glowworms to change the intensity of the luciferin emission and thus appear to glow at different intensities.
1.The GSO algorithm makes the agents glow at intensities approximately proportional to the function value being optimized. It is assumed that glowworms of brighter intensities attract glowworms that have lower intensity.
2.The second significant part of the algorithm incorporates a dynamic decision range by which the effect of distant glowworms are discounted when a glowworm has sufficient number of neighbours or the range goes beyond the range of perception of the glowworms.
The part 2 of the algorithm makes it different from Firefly algorithm
Firefly algorithm
The firefly algorithm is a metaheuristic algorithm, inspired by the flashing behaviour of fireflies. The primary purpose for a firefly's flash is to act as a signal system to attract other fireflies...
where there is no "sufficient number o neighbours" limit and there is no perception limit based on distance.
This two "cognitive limits" allows swarm
Swarm
Swarm behaviour, or swarming, is a collective behaviour exhibited by animals of similar size which aggregate together, perhaps milling about the same spot or perhaps moving en masse or migrating in some direction. As a term, swarming is applied particularly to insects, but can also be applied to...
s of glowworms to split into sub-groups and converge to high function value points. This property of the algorithm allows it to be used to identify multiple peaks of a multi-modal function and makes it part of Evolutionary multi-modal optimization
Evolutionary multi-modal optimization
In applied mathematics, multimodal optimization deals with Optimization tasks that involve finding all or most of the multiple solutions . Knowledge of multiple solutions to an optimization task is especially helpful in engineering, when due to physical constraints, the best results may not...
algorithms family.
The GSO algorithm was developed and introduced by K.N. Krishnanand and D. Ghose in 2005 at the Guidance, Control, and Decision Systems Laboratory in the Department of Aerospace Engineering at the Indian Institute of Science
Indian Institute of Science
Indian Institute of Science is a research institution of higher learning located in Bangalore, India. It was established in 1909.-History:After a chance meeting between Jamsetji N...
, Bangalore
Bangalore
Bengaluru , formerly called Bengaluru is the capital of the Indian state of Karnataka. Bangalore is nicknamed the Garden City and was once called a pensioner's paradise. Located on the Deccan Plateau in the south-eastern part of Karnataka, Bangalore is India's third most populous city and...
, India
India
India , officially the Republic of India , is a country in South Asia. It is the seventh-largest country by geographical area, the second-most populous country with over 1.2 billion people, and the most populous democracy in the world...
. Subsequently, it has been used in various applications and several papers have appeared in the literature using the GSO algorithm.
See also
- MetaheuristicMetaheuristicIn computer science, metaheuristic designates a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. Metaheuristics make few or no assumptions about the problem being optimized and can search very large spaces...
- Firefly algorithmFirefly algorithmThe firefly algorithm is a metaheuristic algorithm, inspired by the flashing behaviour of fireflies. The primary purpose for a firefly's flash is to act as a signal system to attract other fireflies...
(FA) - Evolutionary multi-modal optimizationEvolutionary multi-modal optimizationIn applied mathematics, multimodal optimization deals with Optimization tasks that involve finding all or most of the multiple solutions . Knowledge of multiple solutions to an optimization task is especially helpful in engineering, when due to physical constraints, the best results may not...