An Extended Eigenant Colony System Applied to the Sequential Ordering Problem
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.
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
2014 IEEE Symposium on Swarm Intelligence, SIS 2014 (2014: Dec. 9-12, Orlando, FL)
Electrical and Computer Engineering
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
Article - Conference proceedings
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01 Dec 2014