模糊人工蜂群算法的旅行商问题求解

针对传统人工智能算法早熟收敛问题, 基于模糊化处理和蜂群寻优的特点, 提出一种模糊人工蜂群算法, 将模糊输入/输出机制引入到算法中来保持蜜源访问概率的动态更新。根据算法计算过程中的不同阶段对蜜源访问概率有效调整, 避免算法陷入局部极值。通过对旅行商问题的仿真实验和与其他算法的比较来验证算法的性能。计算结果表明, 该算法有良好的鲁棒性和有效性。

Fuzzy artificial bees colony algorithm for solving traveling salesman problem

Aiming at the premature convergence problem in traditional intelligent optimization algorithm, this paper proposed a fuzzy artificial bees colony algorithm, it based on the principles of fuzzy processing and bees colony behavior. It introduced fuzzy inputs and fuzzy outputs into the algorithm to maintain dynamic updates of the nectar access probability. According to effective adjustment on nectar access probability during the different stages of algorithm calculation, the algorithm avoided local optima. Simulation tests of traveling salesman problem and comparisons with other algorithms show the performance of proposed algorithm. The computational results prove the algorithm is feasible and effective.