Dataset for Ant colony system for the multi objective problems using the collective knowledge center

Published: 14 April 2019| Version 2 | DOI: 10.17632/dt9pnww8z4.2
Mohamed RHAZZAF,


Dataset generated from running the ant colony system for the multi objective problems using the concept of the collective knowledge center, the four SQL dump files indicate the simulation of the ant colony tackling for a 50 random graphs of size equal respectively to 100, and 300 for the process of learning, and then tackling of the two tsp graph file euclideAB100.tsp and euclideAB300.tsp for evaluating the model performance. The learning process and the feeding of the knowledge center is done through the commitment of 110 ants subdivided into 11 groups of 10 ants. The members of the colony share a set of parameters of the MOACS algorithm, namely local and global evaporation respectively ρ, γ, fixed on the value 0.001, an exploitation value q_0= 0.9, and the maximum number of search cycles is 200 cycles.