Page 36 - Fister jr., Iztok, and Andrej Brodnik (eds.). StuCoSReC. Proceedings of the 2016 3rd Student Computer Science Research Conference. Koper: University of Primorska Press, 2016
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le 1: Parallel points between the definition of swarm intelligence and the process of creation of new
nature-inspired algorithms.
Definition of swarm intelligence New nature-inspired algorithm cre-
ation
many individuals many authors
simple actions watching the inspiration in nature,
giving a new name for the algo-
rithm, developing a formula
behavioral actions publishing a paper
complex name motivates other individuals,
new hybrid and adaptive variants
decentralized algorithm is spread all over the
world, impossible to stop spreading
this algorithm – the same as viruses
for example
gorithm creation? The Table 1 shows point to point com- the research community will help drastically in preventing
parison among these two processes. What is the most in- the emergence of new population-based nature-inspired al-
teresting is that the process of new algorithm creation pos- gorithms on new proposal attempts and make this research
sesses the behavior of swarm intelligence. Swarm intelli- area clean again. Finally, the evolution of everything has
gence based algorithms consist of many individuals. On the not been finished in one night, but it took a lot of time.
other hand, the process of population-based nature-inspired Eventually, it could also be the same for population-based
algorithms is guided by many authors. Simple actions (for nature-inspired algorithms.
example foraging in bees or pheromone tracking in ants or
even home building by termites) are, in the process of new 9. REFERENCES
algorithm creation, defined as simple actions where authors
try to find an inspiration in nature, give their algorithm a [1] H.-G. Beyer and H.-P. Schwefel. Evolution
bombastic name and even develop a formula that will mostly strategies–a comprehensive introduction. Natural
guide an evolutionary process. Behavioral actions are, ba- computing, 1(1):3–52, 2002.
sically, connected with publishing a paper in a journal or
at a conference, while complex behavior is connected with [2] P. Clapham. Publish or perish. BioScience,
spreading the algorithm all over the world with the help 55(5):390–391, 2005.
of social media [12, 3] (Twitter, Facebook, Researchgate,
Academia, Google groups, etc.), search engines (Google, Ya- [3] T. D. Cosco. Medical journals, impact and social
hoo), emails (many authors send emails to others attached media: an ecological study of the twittersphere.
with the source code and pdfs), mouth sharing (via confer- Canadian Medical Association Journal,
ences and social meetings) and so on. Decentralized behav- 187(18):1353–1357, 2015.
ior is expressed as an algorithm that is spread all over the
world and it is also impossible to stop it spreading. Espe- [4] M. Dorigo and T. Stu¨tzle. Ant colony optimization:
cially, new researchers take a new algorithm and create new overview and recent advances. Techreport, IRIDIA,
variants (mostly hybrid variants or apply this algorithm on Universite Libre de Bruxelles, 2009.
industrial problems) and then, again, we obtain complex be-
havior. [5] I. Fister Jr., X.-S. Yang, I. Fister, J. Brest, and
D. Fister. A brief review of nature-inspired algorithms
8. CONCLUSION for optimization. Elektrotehniˇski vestnik,
80(3):116–122, 2013.
In this paper we took a view on the new population-based
nature-inspired algorithms‘ development. The new population- [6] S. Fong, X. Wang, Q. Xu, R. Wong, J. Fiaidhi, and
based nature-inspired algorithms are released every month S. Mohammed. Recent advances in metaheuristic
and, basically, they have nothing special and no novel fea- algorithms: Does the makara dragon exist? The
tures for science. Thus, the development of the new population- Journal of Supercomputing, pages 1–23, 2015.
based nature-inspired algorithms may be becoming very dan-
gerous for science. We found that there are many social ten- [7] S. Fong, R. Wong, and P. Pichappan. Debunking the
sions that lead authors towards the new population-based designs of contemporary nature-inspired computing
nature-inspired algorithm creation, especially the wish for algorithms: from moving particles to roaming
quick paper publishing and citations on published papers. elephants. In 2015 Fourth International Conference on
Additionally, our research revealed that the process of the Future Generation Communication Technology
new population-based nature-inspired algorithm possesses (FGCT), pages 1–11. IEEE, 2015.
the behavior of the swarm intelligence paradigm. Thus, it
would not be easy to stop the invasions of the new population- [8] F. Glover. Future paths for integer programming and
based nature-inspired algorithms in the near future (only links to artificial intelligence. Computers & operations
a systematic approach can help). However, awareness of research, 13(5):533–549, 1986.
[9] F. Glover. Tabu search–part i. ORSA Journal on
computing, 1(3):190–206, 1989.
[10] F. Glover. Tabu search–part ii. ORSA Journal on
computing, 2(1):4–32, 1990.
[11] F. Glover and K. S¨orensen. Metaheuristics.
Scholarpedia, 10(4), 2015.
StuCoSReC Proceedings of the 2016 3rd Student Computer Science Research Conference 36
Ljubljana, Slovenia, 12 October
nature-inspired algorithms.
Definition of swarm intelligence New nature-inspired algorithm cre-
ation
many individuals many authors
simple actions watching the inspiration in nature,
giving a new name for the algo-
rithm, developing a formula
behavioral actions publishing a paper
complex name motivates other individuals,
new hybrid and adaptive variants
decentralized algorithm is spread all over the
world, impossible to stop spreading
this algorithm – the same as viruses
for example
gorithm creation? The Table 1 shows point to point com- the research community will help drastically in preventing
parison among these two processes. What is the most in- the emergence of new population-based nature-inspired al-
teresting is that the process of new algorithm creation pos- gorithms on new proposal attempts and make this research
sesses the behavior of swarm intelligence. Swarm intelli- area clean again. Finally, the evolution of everything has
gence based algorithms consist of many individuals. On the not been finished in one night, but it took a lot of time.
other hand, the process of population-based nature-inspired Eventually, it could also be the same for population-based
algorithms is guided by many authors. Simple actions (for nature-inspired algorithms.
example foraging in bees or pheromone tracking in ants or
even home building by termites) are, in the process of new 9. REFERENCES
algorithm creation, defined as simple actions where authors
try to find an inspiration in nature, give their algorithm a [1] H.-G. Beyer and H.-P. Schwefel. Evolution
bombastic name and even develop a formula that will mostly strategies–a comprehensive introduction. Natural
guide an evolutionary process. Behavioral actions are, ba- computing, 1(1):3–52, 2002.
sically, connected with publishing a paper in a journal or
at a conference, while complex behavior is connected with [2] P. Clapham. Publish or perish. BioScience,
spreading the algorithm all over the world with the help 55(5):390–391, 2005.
of social media [12, 3] (Twitter, Facebook, Researchgate,
Academia, Google groups, etc.), search engines (Google, Ya- [3] T. D. Cosco. Medical journals, impact and social
hoo), emails (many authors send emails to others attached media: an ecological study of the twittersphere.
with the source code and pdfs), mouth sharing (via confer- Canadian Medical Association Journal,
ences and social meetings) and so on. Decentralized behav- 187(18):1353–1357, 2015.
ior is expressed as an algorithm that is spread all over the
world and it is also impossible to stop it spreading. Espe- [4] M. Dorigo and T. Stu¨tzle. Ant colony optimization:
cially, new researchers take a new algorithm and create new overview and recent advances. Techreport, IRIDIA,
variants (mostly hybrid variants or apply this algorithm on Universite Libre de Bruxelles, 2009.
industrial problems) and then, again, we obtain complex be-
havior. [5] I. Fister Jr., X.-S. Yang, I. Fister, J. Brest, and
D. Fister. A brief review of nature-inspired algorithms
8. CONCLUSION for optimization. Elektrotehniˇski vestnik,
80(3):116–122, 2013.
In this paper we took a view on the new population-based
nature-inspired algorithms‘ development. The new population- [6] S. Fong, X. Wang, Q. Xu, R. Wong, J. Fiaidhi, and
based nature-inspired algorithms are released every month S. Mohammed. Recent advances in metaheuristic
and, basically, they have nothing special and no novel fea- algorithms: Does the makara dragon exist? The
tures for science. Thus, the development of the new population- Journal of Supercomputing, pages 1–23, 2015.
based nature-inspired algorithms may be becoming very dan-
gerous for science. We found that there are many social ten- [7] S. Fong, R. Wong, and P. Pichappan. Debunking the
sions that lead authors towards the new population-based designs of contemporary nature-inspired computing
nature-inspired algorithm creation, especially the wish for algorithms: from moving particles to roaming
quick paper publishing and citations on published papers. elephants. In 2015 Fourth International Conference on
Additionally, our research revealed that the process of the Future Generation Communication Technology
new population-based nature-inspired algorithm possesses (FGCT), pages 1–11. IEEE, 2015.
the behavior of the swarm intelligence paradigm. Thus, it
would not be easy to stop the invasions of the new population- [8] F. Glover. Future paths for integer programming and
based nature-inspired algorithms in the near future (only links to artificial intelligence. Computers & operations
a systematic approach can help). However, awareness of research, 13(5):533–549, 1986.
[9] F. Glover. Tabu search–part i. ORSA Journal on
computing, 1(3):190–206, 1989.
[10] F. Glover. Tabu search–part ii. ORSA Journal on
computing, 2(1):4–32, 1990.
[11] F. Glover and K. S¨orensen. Metaheuristics.
Scholarpedia, 10(4), 2015.
StuCoSReC Proceedings of the 2016 3rd Student Computer Science Research Conference 36
Ljubljana, Slovenia, 12 October
