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An Improved Genetic Algorithm for the Optimal Distribution of Fresh Products under Uncertain Demand

Author

Listed:
  • Hao Zhang

    (School of Business, Beijing Technology and Business University, Beijing 100048, China)

  • Yan Cui

    (School of Business, Beijing Technology and Business University, Beijing 100048, China)

  • Hepu Deng

    (School of Accounting, Information Systems and Supply Chain, RMIT University, Melbourne, VIC 3149, Australia)

  • Shuxian Cui

    (School of Business, Beijing Technology and Business University, Beijing 100048, China)

  • Huijia Mu

    (School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China)

Abstract

There are increasing challenges for optimally distributing fresh products while adequately considering the uncertain demand of customers and maintaining the freshness of products. Taking the nature of fresh products and the characteristics of urban logistics systems into consideration, this paper proposes an improved genetic algorithm for effectively solving this problem in a computationally efficient manner. Such an algorithm can adequately account for the uncertain demand of customers to select the optimal distribution route to ensure the freshness of the product while minimizing the total distribution cost. Iterative optimization procedures are utilized for determining the optimal route by reducing the complexity of the computation in the search for an optimal solution. An illustrative example is presented that shows the improved algorithm is more effective with respect to the distribution cost, the distribution efficiency, and the distribution system’s reliability in optimally distributing fresh products.

Suggested Citation

  • Hao Zhang & Yan Cui & Hepu Deng & Shuxian Cui & Huijia Mu, 2021. "An Improved Genetic Algorithm for the Optimal Distribution of Fresh Products under Uncertain Demand," Mathematics, MDPI, vol. 9(18), pages 1-18, September.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:18:p:2233-:d:633572
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    References listed on IDEAS

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