This paper combines the development situation of blue carbon industry to formulate the multi-dimensional optimization model construction of blue carbon industry cluster path. First set the model decision variables and objective function, and divide the constraints. Select the genetic algorithm to solve the optimization model. Determine the research data sources and genetic algorithm parameters, and analyze the multidimensional optimization model. The sensitivity coefficients of each decision variable to the optimization model are 0.2~0.1, and its sensitivity level is III, which means that the selected decision variables meet the research requirements. Compared with the other three algorithms, this paper’s genetic algorithm has superiority in four performance indicators, indicating that the genetic algorithm is more suitable for optimization model solving, and finally, the optimization model of this paper is put into the actual blue carbon industry, and it is found that there is a significant difference in the effect of carbon reduction, economic gain, green environmental protection, and satisfaction before and after the optimization (P<0.05), which verifies the effectiveness of this paper's optimization for practical application, and finally, according to the optimization results, the Finally, according to the optimization results, the corresponding optimization path is proposed.