Yao Wang
Circular economy, logistics assembly line, intelligent distribution, taboo search algorithm, particle swarm optimisation algorithm
The establishment of an effective, stable, and energy-saving intelligent distribution (ID) model has emerged as a hot research topic. Cyclic ID is one of the necessary ways to improve production efficiency and distribution economy due to the large-scale and highly integrated assembly lines of modern production enterprises. In light of this, the research creates a two-stage cyclic ID model for the cyclic distribution and automatic guided vehicle scheduling problems by combining the double-cycle material distribution model with the taboo search method. The final experimental findings reveal that the model in the 1:2:3, 1:2:1, and 1:1:1 three models ratio of the final temporary inventory average occupancy maintained in the range of 40% to 60% of the safe level, and energy saving efficiency of the minimum and maximum value of about 20% and 40%. As a result, the two-stage ID model’s average time ranges from 8 s to 25 s, while the traditional particle swarm optimisation algorithm’s average time ranges from 19 s to 40 s. This means that the two-stage ID model’s average time is approximately 50% faster than that of the traditional particle swarm optimisation algorithm. The experimental results demonstrate the viability and applicability of the suggested two- stage ID model in terms of energy-saving effectiveness, operational effectiveness, and stability.
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