Multi-target job shop energy-saving optimization method based on U-NSGA-III algorithm

The invention discloses a multi-target job shop energy-saving optimization method based on a U-NSGA-III algorithm. The method comprises the following steps: 1) setting an initial iteration frequency and a maximum iteration frequency; 2) generating an initial population as a parent; 3) selecting excellent chromosomes from the parent population for chromosome crossover and mutation processing; 4) iteration times + 1; 5) combining the parent chromosome with a filial generation chromosome population generated by crossover and mutation processing; 6) sequencing the combined chromosomes to generatea new solution set, if the solution set can be determined in the step 6), executing the step 8), and if the solution set cannot be determined in the step 6), executing the step 7); 7) calculating to obtain chromosomes which are not determined in the step 6) in the solution set, and finally determining the solution set; 8) judging a circulation condition, and jumping out of an algorithm circulationoutput result if the circ