基于动态双种群的黏菌和花粉混合算法OA北大核心CSTPCD

Aiming at overcoming drawbacks of imbalance between the global and local search ability of a single heuristic algo-rithm,this paper proposed a slime mould and flower pollination hybrid algorithm based on dynamic dual population,named HASMFP.Firstly,HASMFP adopted a grouping mechanism that took the distance between individual inside population and the current optimal individual into consideration to dynamically divide whole population into slime mold subpopulation and pol-len subpopulation to balance the exploration and development capabilities of the algorithm more effectively.Secondly,HASMFP used a ranking mechanism based on similarity and fitness to improve diversity of slime mold population,and further increased the probability to jump out of local optimal.Finally,HASMFP also adopted a dynamic weights and constant shrin-kage coefficients with an elite guidance terms to further enhance the local and global search ability of standard flower pollina-tion algorithm at the same time.It used 12 test functions from CEC2017 test suit as the testbed to evaluate the performance of HASMFP with other 5 algorithms:ISMA,DTSMA,HLFPA,SCFPA,and tMFPA.It conducted ablation experiments to eva-luate the effectiveness of all improvement strategies applied in HASMFP.Experimental result shows that HASMFP can rank first under the combination of all improvement strategies.The result of Friedman test based on experimental data illustrates that HASMFP can achieve the supreme performance among all evaluated algorithms.