Title :
Design and Classification of Ant Metaheuristics
Author :
Zufferey, Nicolas
Author_Institution :
HEC, Univ. of Geneva, Geneva, Switzerland
Abstract :
Ant algorithms are well-known metaheuristics which have been widely studied and used since two decades. Generally, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: the discussion is thus not limited by the common framework of the constructive ant algorithms. The goal of this paper is on the one hand to classify and benchmark the ant algorithms, and on the other hand to put forward the successful elements of these methods. Moreover, the performance of the different types of ant algorithms is evaluated according to several criteria, and not only according to the quality of the obtained solutions.
Keywords :
ant colony optimisation; ant metaheuristics algorithm; constructive ant algorithms; Algorithm design and analysis; Classification algorithms; Equations; Force; Heuristic algorithms; Optimization; Robustness; ant algorithms; population-based metaheuristics;
Conference_Titel :
Parallel, Distributed and Network-Based Processing (PDP), 2014 22nd Euromicro International Conference on
Conference_Location :
Torino
DOI :
10.1109/PDP.2014.69