InterCriteria Analysis of ACO start startegies

Stefka Fidanova , Olympia Roeva , Paweł Gepner , Marcin Paprzycki

Abstract

In combinatorial optimization, the goal is to find the optimal object from a finite set. Since such problems are hard to be solved, usually some metaheuristics is applied. One of the most successful techniques for a number of classes of problems is Ant Colony Optimization (ACO). Some start strategies can be applied, to the ACO algorithms, to improve their performance. Here, the InterCriteria Analysis (ICrA) is applied to the ACO algorithm. On the basis of the ICrA, we examine and analyse the ACO performance according to the different start strategies.

Author Stefka Fidanova - [Institute of Information and IICT Bulgarian Acadmey of Sciences]
Stefka Fidanova,,
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, Olympia Roeva - [Institute of Information and IICT Bulgarian Acadmey of Sciences]
Olympia Roeva,,
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, Paweł Gepner (FPE / IOPS)
Paweł Gepner,,
- The Institute of Organization of Production Systems
, Marcin Paprzycki - Systems Research Institute. Polish Academy of Science [Polish Academy of Sciences]
Marcin Paprzycki ,,
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Journal seriesAnnals of Computer Science and Information Systems, ISSN 2300-5963
Issue year2016
VolProceedings of the 2016 Federated Conference on Computer Science and Information Systems
No8
Pages547-550
Publication size in sheets0.5
ConferenceFederated Conference on Computer Science and Information Systems (FedCSIS 2016), 11-09-2016 - 14-09-2016, Gdańsk, Polska
DOIDOI:10.15439/2016F137
Languageen angielski
Score (nominal)15
Score sourceconferenceIndex
ScoreMinisterial score = 15.0, 18-09-2020, ArticleFromJournalAndMatConfByIndicator
Ministerial score (2013-2016) = 15.0, 18-09-2020, ArticleFromJournalAndMatConfByIndicator
Publication indicators Scopus Citations = 13; WoS Citations = 4; GS Citations = 16.0
Citation count*16 (2020-08-31)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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