Abstract
The algorithm proposed in this paper conceives the process of solving optimization problems as a process in which an infectious disease spreads among several individuals in an ecosystem. Its propagation law can be described by the SIR infectious disease model. Infectious diseases attack certain locations in several disease-causing genes of individuals. For different individuals, which disease genes and which sites are attacked are completely random; if an individual is cured, which immune genes and which sites are immunized are also completely random. Because of the problem of determining the growth rate of the number of infectious diseases, and improved SIR model is established, combined with historical data to quantitatively predict the future growth rate of the number of infected people, to formulate corresponding disease prevention and control measures.
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