An Extended Eigenant Colony System Applied to the Sequential Ordering Problem
Abstract
The EigenAnt Ant Colony System (EAAS) model is an Ant Colony Optimization (ACO) model based on the EigenAnt algorithm. In previous work, EAAS was found to perform competitively with the Enhanced Ant Colony System (EACS) algorithm, a state-of-the-art method for the Sequential Ordering Problem (SOP). In this paper, we extend EAAS by increasing the amount of stochasticity in its solution construction procedure. In experimental results on the SOPLIB instance library, we find that our proposed method, called Probabilistic EAAS (PEAAS), performs better than both EAAS and EACS. The non-parametric Friedman test is applied to determine statistical significance.
Recommended Citation
A. Ezzat et al., "An Extended Eigenant Colony System Applied to the Sequential Ordering Problem," Proceedings of the 2014 IEEE Symposium on Swarm Intelligence (2014, Orlando, FL), Institute of Electrical and Electronics Engineers (IEEE), Dec 2014.
The definitive version is available at https://doi.org/10.1109/SIS.2014.7011806
Meeting Name
2014 IEEE Symposium on Swarm Intelligence, SIS 2014 (2014: Dec. 9-12, Orlando, FL)
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Center for High Performance Computing Research
Keywords and Phrases
Algorithms; Artificial Intelligence; Ant Colony Optimization (ACO); Ant Colony Systems; Construction Procedures; Model-Based OPC; Non-Parametric; Sequential Ordering Problems; State-Of-The-Art Methods; Statistical Significance; Ant Colony Optimization
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2014 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Dec 2014
