INTELLIGENT DISTRIBUTION OPTIMISATION MODEL OF LOGISTICS ASSEMBLY LINE FOR CIRCULAR ECONOMY

Yao Wang

Keywords

Circular economy, logistics assembly line, intelligent distribution, taboo search algorithm, particle swarm optimisation algorithm

Abstract

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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