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January 1, 2026International Journal of Computing Science and Mathematics

Intelligent Cigarette Loading Optimisation for Cost-Effectiveness and Low-Carbon Logistics

Yi Lu Zixia Chen Hao Chen Xiaoping Chen

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Key Points

The aim is to enhance the efficiency of cigarette loading processes while minimizing carbon footprint.
Focused on logistic optimization strategies
Examined cost metrics in cigarette supply chains
Analyzed environmental impacts of loading techniques
Identified cost-effective practices in logistics
Demonstrated improved sustainability through optimized loading
Highlighted potential reductions in carbon emissions

Implication

Intelligent cigarette loading improves cost-effectiveness in logistics, highlighting a more sustainable approach.

Abstract

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Cite This Study

Lu et al. (2026) studied this question.

synapsesocial.com/papers/69c08b9fa48f6b84677f90ee https://doi.org/10.1504/ijcsm.2026.10077194

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