A multi-user interactive genetic algorithm and its application in group design

General interactive genetic algorithms allow only one user to participate in evaluation for candidate solutions, so their results can only reflect one users preference. But we should try to meet as many users needs as possible when designing products. To solve this problem, a multi-user interactive genetic algorithm (MUIGA) applicable for group design was proposed. And the detailed design of the three key modules-population initialization module, single-population module and multi-population module was given. Finally, the proposed algorithm and the general single-user interactive genetic algorithm were applied to a fashion design system, respectively. The experimental results were compared to validate the feasibility of MUIGA in group design.