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Developing and solving an integrated model for production routing in sustainable closed-loop supply chain

机译:开发和解决可持续闭环供应链中生产路线的集成模型

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Social and environmental sustainability has gained increasing importance in today & rsquo;s complex supply chains. Accordingly, an integrated model for production routing in the sustainable closed-loop supply chain is presented in the current study. A three-objective mathematical model is also proposed to minimize supply chain costs, maximize social responsibility or social benefits, and finally, minimize environmental emissions. Sample trial problems are solved in three groups of the small, medium, and large size using the BCO algorithm. To prove the efficiency of this algorithm, its results are compared with the results using the NSGA-II algorithm in terms of comparative metrics such as quality, diversity, and spacing, as well as the runtime to the solution. According to the results, in all cases, the BCO algorithm outperformed the NSGA-II algorithm as it achieved more qualitative and near-optimal solutions. Also, the diversity metric values showed that the BCO algorithm is stronger in the exploration and extraction of the solution feasible region. The results of the metric of spacing and runtime to solution also showed that the NSGA-II algorithm achieves the solution in lower runtime than the BCO algorithm and searches solutions space in a more uniform manner.(c) 2021 Elsevier Ltd. All rights reserved.
机译:社会和环境可持续性在今天和rsquo的复杂供应链中取得了越来越重要。因此,在当前研究中介绍了可持续闭环供应链中的生产路由的集成模型。还提出了一个三目标的数学模型,以最大限度地减少供应链成本,最大化社会责任或社会效益,最终减少环境排放。使用BCO算法,在三组小,介质和大尺寸中解决了样本试验问题。为了证明该算法的效率,将其结果与使用NSGA-II算法的结果进行比较,例如质量,多样性和间隔,以及解决方案的运行时间。根据结果​​,在所有情况下,BCO算法优于NSGA-II算法,因为它取得了更具定性和近最优的解决方案。此外,分集度量值表明,BCO算法在解决方案可行区域的勘探和提取方面较强。间距和运行时间的度量结果也表明,NSGA-II算法在更低的运行时间内实现了比BCO算法更低的解决方案,并以更统一的方式搜索解决方案空间。(c)2021 elestvier有限公司保留所有权利。

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