Garbage Classification Game Based on Bilevel Multi-objective Optimization with Fuzzy Weight

Nowadays, the bilevel multi-objective optimization problem has been received extensive attention from scholars. As two mainstream algorithms to solve it, intelligent algorithm and interactive algorithm based on satisfaction have disadvantages such as slow operation speed and too much subjectivity in weight selection, respectively. This paper proposes a multi-attribute decision-making method based on fuzzy weight, which is a natural generalization of deterministic weight, and it can cope with the decision-making risks brought by uncertain environment, which has strong robustness. Meanwhile the new deviation function index proposed could reflect that the upper and lower decision-makers execute the final decision with the same enthusiasm, which is convenient to make exploratory decisions in unknown environment. Finally, compared with the traditional existing methods, the effectiveness of the proposed method and indicator is verified by the garbage classification game in the main urban district of Chongqing.