标题：LOCATION AND PATH OPTIMIZATION OF GREEN COLD
CHAIN LOGISTICS BASED ON IMPROVED GENETIC
ALGORITHM FROM THE PERSPECTIVE OF LOW CARBON
AND ENVIRONMENTAL PROTECTION
摘要：Aiming at the distribution efficiency and cost of cold chain logistics of fresh products, a solution to the location-path optimization problem of green cold chain logistics using an improved genetic algo- rithm from the perspective of low-carbon environ-mental protection is proposed. First, considering transportation costs, fixed costs, refrigeration costs, and time penalty costs, increase carbon emission costs and cargo damage costs to build a cold chain logistics model. Then, combining the specific model of the optimization problem to improve the genetic algorithm, including the coding method, genetic op- erator and fitness function, etc., the linear adaptive cross-mutation strategy is introduced to dynamically djust the genetic operator. Finally, the improved ge- netic algorithm is used to solve the cold chain logis- tics optimization problem to effectively reduce car- bon emissions and cost in the cold chain distribution process. Using actual cold chain logistics and distri- bution data, the proposed method is verified basedon the Matlab platform. The results show that com- pared with other methods, the proposed method ac- celerates the convergence speed, reduces the distri- bution cost, and realizes a low-carbon economy.
