针对几种元启发式算法的应用性能对比研究

随着智能制造和精益生产的推进,元启发式算法(智能算法)已经在实际工业和生活中得到了广泛应用。然而,由于其自身结构所带来的不确定性,如何针对具体目标快速选择一个高效的特定算法,仍然需要进一步的研究与探讨。为此以具有代表性的NP-hard问题—TSP问题为例,针对典型的元启发式算法:遗传算法、模拟退火算法、禁忌搜索算法和蚁群算法进行了不同维度的实验与对比。并结合算法的不同求解思想,通过对其计算结果和计算过程的定量分析,给出了四种算法的特点与异同,以此来为相关算法的选择、应用以及改进提供基础与参考。

Comparative Study on Application Performance of Several Meta-Heuristic Algorithms

With the development of intelligent manufacturing and lean production,the meta-heuristic algorithms(intelligent algorithms)have been widely used in industry and life.However,due to the uncertainty caused by their structures,it is still an urgent problem how to choose an efficient algorithm for the specific target.In this study,a series of experiments based on TSP problems were conducted on four typical meta-heuristic algorithms,including genetic algorithm,simulated annealing,Tabu search and ant colony optimization.Through the quantitative analysis on calculation process and results,the characteristics and differences of these algorithms were given.Therefore,the contribution of this work is to provide the basis and reference for the selection,application and improvement of the corresponding algorithms.