Optimization of green logistics distribution scheme based on artificial bee colony algorithm

Under the dual drive of consumption upgrading and low-carbon economy, this study proposed an improved artificial bee swarm algorithm (IFW-ABC) to solve the spatio-temporal constraints and multi-objective optimization problems of green logistics. By constructing a multi-dimensional optimization model including carbon emission cost, quality loss cost and dynamic penalty mechanism, the discrete solution spatial coding scheme and adaptive search mechanism are innovatively designed. The model experiment took 15 retail terminals in a city as samples to compare the optimization efficiency of traditional ABC, FW-ABC and IFW-ABC algorithms. The results show that the total cost of IFW-ABC is 7358.93 yuan when considering the constraint of green emission, which is 8.15% lower than the traditional algorithm, and the proportion of quality loss cost is reduced to 9.87%, and a more intensive distribution route topology is formed. The results of this study show that the algorithm improvement effectively balances the three objectives of timeliness, economy and environmental friendliness of green logistics, and provides a quantifiable decision support tool for the intelligent transformation of green supply chain.