Title

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.

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.

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