The invention provides an antibody calculation optimization method based on a genetic algorithm. The method covers algorithms such as peptide chain processing, epitope recognition, sequence annotation, CDR H3 sequence design, antibody modeling, molecular docking, antibody property evaluation and the like, and has a full-process automatic antibody design function. Based on known antibody sequence data, a variant antibody sequence formed by combining random sites and random residues is iteratively generated and evaluated by utilizing a genetic algorithm aiming at a heavy-chain highly variable H3section (CDR H3) of the antibody and is subjected to comprehensive scoring comparison with an original antibody, so that an optimized antibody is obtained or a low-quality antibody is removed, and finally, a candidate antibody sequence library is generated, and the biophysical property of the candidate antibody is predicted. According to the invention, basic elements of an antibody calculation optimization process are integrated, and automation of the process is realized on the same platform.