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An Adaptive Nutcracker Optimization Approach for Distribution of Fresh Agricultural Products with Dynamic Demands

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  • Daqing Wu

    (College of Economics and Management, Shanghai Ocean University, Shanghai 201306, China
    Department of Nanchang Technology, 901 Yingxiong Dadao, Economic and Technological Development Zone, Nanchang 330044, China
    These authors contributed equally to this work.)

  • Rong Yan

    (College of Economics and Management, Shanghai Ocean University, Shanghai 201306, China
    These authors contributed equally to this work.)

  • Hongtao Jin

    (College of Economics and Management, Shanghai Ocean University, Shanghai 201306, China)

  • Fengmao Cai

    (Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield S37AZ, UK)

Abstract

In the operational, strategic and tactical decision-making problems of the agri-food supply chain, the perishable nature of the commodities can represent a particular complexity problem. It is, therefore, appropriate to consider decision support tools that take into account the characteristics of the products, the needs and the requirements of producers, sellers and consumers. This paper presents a green vehicle routing model for fresh agricultural product distribution and designs an adaptive hybrid nutcracker optimization algorithm (AH-NOA) based on k-means clustering to solve the problem. In the process, the AH-NOA uses the CW algorithm to increase population diversity and adds genetic operators and local search operators to enhance the global search ability for nutcracker optimization. Finally, the experimental data show that the proposed approaches effectively avoid local optima, promote population diversity and reduce total costs and carbon emission costs.

Suggested Citation

  • Daqing Wu & Rong Yan & Hongtao Jin & Fengmao Cai, 2023. "An Adaptive Nutcracker Optimization Approach for Distribution of Fresh Agricultural Products with Dynamic Demands," Agriculture, MDPI, vol. 13(7), pages 1-21, July.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:7:p:1430-:d:1197899
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    References listed on IDEAS

    as
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