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

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.本数据集基于集体知识中心理念，针对多目标问题运行蚁群系统生成。四个SQL转储文件（SQL dump）用于模拟蚁群的求解流程：学习阶段针对50张随机图开展求解，其规模分别为100与300；后续通过两份旅行商问题（Traveling Salesman Problem，TSP）图文件euclideAB100.tsp与euclideAB300.tsp完成模型性能评估。 本次实验的蚁群共部署110只蚂蚁，划分为11组，每组10只，以此完成学习流程与知识中心的信息馈送。该蚁群群体共享多目标蚁群系统（Multi Objective Ant Colony System，MOACS）的一组算法参数：局部蒸发系数ρ与全局蒸发系数γ均固定为0.001，探索利用系数q₀=0.9，最大搜索轮次为200轮。