Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: As a novel particles swarm optimization algorithm, r/KPSO takes the advantages of r-selection and K selection. Particles in high fitness (K-subswarm called in this paper) perform K-selection. K-subswarm only can produce few progenies but the progenies are nurtured delicately with much parent care. On the other hand, r-selection is performed for other particles in relatively low fitness (r-subswarm called). r-subswarm can produce a large number of progenies with little parent care and the progenies have to compete for survival according to fitness and only the best ones can survive. In r/KPSO, the particles performed r-selection mainly explore the search space as possible as they can to find more potential solutions in large speed, and those particles performed K-selection keep the current optimum solutions and exploit the space as they can to find more ideal solutions. To evaluate convergence speed quantitatively, a novel criterion named first converging generation (FCG) is introduced. Experiments re conducted on standard benchmark functions, and experimental results shod r/KPSO could converge in higher speed in terms of FCG and in higher precision than standard PSO (SPSO).
['Yunyi Yan', 'Baolong Guo']
I am writing a research paper on a idea Convergence Analysis of PSO Inspired by r- and K-Selection
[{"from": "human", "value": "I am writing a research paper on a idea Convergence Analysis of PSO Inspired by r- and K-Selection"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: As a novel particles swarm optimization algorithm, r/KPSO takes the advantages of r-selection and K selection. Particles in high fitness (K-subswarm called in this paper) perform K-selection. K-subswarm only can produce few progenies but the progenies are nurtured delicately with much parent care. On the other hand, r-selection is performed for other particles in relatively low fitness (r-subswarm called). r-subswarm can produce a large number of progenies with little parent care and the progenies have to compete for survival according to fitness and only the best ones can survive. In r/KPSO, the particles performed r-selection mainly explore the search space as possible as they can to find more potential solutions in large speed, and those particles performed K-selection keep the current optimum solutions and exploit the space as they can to find more ideal solutions. To evaluate convergence speed quantitatively, a novel criterion named first converging generation (FCG) is introduced. Experiments re conducted on standard benchmark functions, and experimental results shod r/KPSO could converge in higher speed in terms of FCG and in higher precision than standard PSO (SPSO)."}]