Abstract
The cold chain logistics (CCL) distribution have been studied by considering customer satisfaction, we propose a multi-objective CCL model with the goals of minimal carbon transaction cost, minimal network cost and maximal customer satisfaction. According to the characteristics of the model, an improved Multi-Objective algorithm was designed, which integrates the dynamic crowding distance and differential mutation operator into non-dominated sorting genetic algorithm II (DDNSGA-II). The DDNSGA-II enhances the diversity of the initial population, the local search ability and search accuracy. Finally, the experimental data show that the proposed approaches effectively increase the customer satisfaction, reduce total distribution costs, and promote energy conservation and emission reduction.
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