Abstract

Aiming at the path optimization problem of pharmaceutical green logistics distribution, a green logistics path optimization model is designed considering constraints such as time window limitation and vehicle capacity, with the optimization objective of minimizing the sum of vehicle transportation cost, overtime cost and green cost, and the constructed model is solved by using genetic algorithm. The constructed model and designed algorithm are verified by actual distribution data. The example experiments show that the genetic algorithm has better solution quality, higher efficiency and more stable results in solving the vehicle path problem at large-scale customer locations. The research results not only expand the vehicle path problem, but also provide decision-making reference for the distribution optimization of related express logistics enterprises.

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