InterCriteria Analysis of ACO start startegies
Stefka Fidanova , Olympia Roeva , Paweł Gepner , Marcin Paprzycki
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.
|Journal series||Annals of Computer Science and Information Systems, ISSN 2300-5963|
|Vol||Proceedings of the 2016 Federated Conference on Computer Science and Information Systems|
|Publication size in sheets||0.5|
|Conference||Federated Conference on Computer Science and Information Systems (FedCSIS 2016), 11-09-2016 - 14-09-2016, Gdańsk, Polska|
|Score|| = 15.0, 18-09-2020, ArticleFromJournalAndMatConfByIndicator|
= 15.0, 18-09-2020, ArticleFromJournalAndMatConfByIndicator
|Publication indicators||= 13; = 4; = 16.0|
|Citation count*||16 (2020-08-31)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.