A Snowmelt Optimization Algorithm Applied to Green Low Carbon Logistics Pathways Optimization Problems

Chunxia Zhai

doi:10.4108/ew.4889

Authors

Chunxia Zhai Department of Logistics Management School of Humanities and Management Xi’an Traffic Engineering Institute, Xi’an 710300, Shaanxi, China

DOI:

https://doi.org/10.4108/ew.4889

Keywords:

green low-carbon logistics path optimization, snow-melt optimization algorithm, position-order array coding, distribution path scheme

Abstract

INTRODUCTION: Efficient and accurate optimization of green and low-carbon logistics paths, as one of the key technologies of green and low-carbon logistics, can not only promote the high-quality development of the economy, but also reduce the negative impacts of logistics on the environment and increase the cost of logistics delivery.

OBJECTIVES: To address the problems of slow convergence and easy to fall into local optimization in the current performance prediction research on talent team building.

METHODS: This paper proposes a snowmelt heuristic optimization algorithm to solve the green low-carbon logistics path optimization problem. Firstly, the objective function of green low-carbon logistics path optimization is designed by analyzing the optimization cost and conditional constraints of the green low-carbon logistics path optimization problem; then, a method based on intelligent optimization algorithm is proposed by designing the position-order array coding and fitness function, combined with the snow-melting optimization algorithm; finally, the validity and superiority of the proposed method are verified by simulation experiments.

RESULTS: The results show that the proposed method not only improves the convergence speed but also increases the optimization fitness value.

Conclusion: The problem of slow convergence and easy to fall into local optimum in the solution of green low-carbon logistics path optimization problem is solved.

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