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首页> 外文期刊>Journal of Cleaner Production >Accounting for uncertainty in eco-efflcient agri-food supply chains: A case study for mushroom production planning
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Accounting for uncertainty in eco-efflcient agri-food supply chains: A case study for mushroom production planning

机译：解释生态高效农业食品供应链中的不确定性：蘑菇生产计划的案例研究

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摘要

Due to the increasing awareness of climate change, depletion of natural resources, and increasing world population, companies in the agri-food sector need to redesign their existing supply chains and take into account both the economic and environmental impact of their operations. In practice not all the required information is available in advance due to various sources of uncertainty in agri-food supply chains. In this research a multi-objective two-stage stochastic programming model is proposed to analyse and evaluate the economic and environmental impacts to account for uncertainty in agri-food supply chains. A mushroom supply chain in the Netherlands is presented as an illustrative case study. Optimal production planning decisions calculated with a two-stage stochastic programming model are compared with the results of an equivalent deterministic model. The results of the optimizations show that accounting for stochasticity in important model parameters can reduce the difference between expected and realized economic performance by approximately 4% on average. Moreover, this paper demonstrates that including stochastic model parameters can reduce the environmental impact without compromising the current economic performance. Given the assumptions in the setup of the case study and the available information, it is concluded that applying a 2-stage stochastic programming approach for production planning decisions can lead to improved economic and environmental performance in an agri-food supply chain. New findings in real-life case studies are needed to get profound insights and understanding on the impact of uncertainty on production planning decisions in sustainable agri-food supply chains. (C) 2019 Elsevier Ltd. All rights reserved.
机译：由于对气候变化，自然资源枯竭和世界人口日益增长的认识不断提高，农业食品领域的公司需要重新设计其现有的供应链，并考虑其运营对经济和环境的影响。实际上，由于农业食品供应链中各种不确定性来源，并非所有必需的信息都可以提前获得。在这项研究中，提出了一个多目标的两阶段随机规划模型来分析和评估经济和环境影响，以解决农产品供应链中的不确定性。介绍了荷兰的蘑菇供应链，作为一个案例研究。将两阶段随机规划模型计算出的最佳生产计划决策与等效确定性模型的结果进行比较。优化结果表明，在重要模型参数中考虑随机性可以使预期和实际经济表现之间的差异平均减少约4％。此外，本文证明，包含随机模型参数可以减少环境影响，而不会损害当前的经济绩效。考虑到案例研究中的假设和可用的信息，得出的结论是，对生产计划决策采用两阶段随机规划方法可以改善农业食品供应链中的经济和环境绩效。需要在现实生活中进行案例研究的新发现，以便获得深刻的见解和认识，以了解不确定性对可持续农业食品供应链中生产计划决策的影响。 （C）2019 Elsevier Ltd.保留所有权利。

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