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Demand-dependent recovery decision-making of a batch of products for sustainability
International Journal of Production Economics ( IF 9.8 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.ijpe.2019.107552
Kai Meng , Ying Cao , Xianghui Peng , Victor Prybutok , Varun Gupta

Abstract This research examines the demand-dependent product recovery decision-making problem for a batch of products that undergo remanufacturing/dismantling via a hybrid recovery system. Product recovery provides an attractive approach to achieving sustainable manufacturing. Faced with changing demand, flexible recovery decisions on product recovery strategies, component recovery options, and recovery yields are critical to enable a successful and sustainable operations. However, a need exists for an integrated model to provide a comprehensive optimal solution from the integrated perspective of economic, environmental, and societal sustainability. This research gap is addressed by proposing and validating a multi-objective decision-making model. Demand-dependent optimal solutions are identified that balance different sustainable performance constraints. Further, a two-stage meta-heuristic method is developed to solve the model, where a cooperative evolution mechanism is designed to optimize dismantling decisions and recovery yields simultaneously. Numerical experiments are conducted that illustrate and validate the developed solution. In addition, the impacts of demand on optimal decisions and different sustainable performance are investigated. The results verify the effectiveness of our new model and approach in assisting decision makers in finding a flexible path to sustainable recovery while providing insights into analyzing the counteraction effect of different demands in hybrid recovery implementation.

中文翻译:

一批产品的可持续需求依赖回收决策

摘要 本研究考察了通过混合回收系统进行再制造/拆解的一批产品的需求依赖型产品回收决策问题。产品回收为实现可持续制造提供了一种有吸引力的方法。面对不断变化的需求,关于产品回收策略、组件回收选项和回收率的灵活回收决策对于实现成功和可持续的运营至关重要。然而,需要一种综合模型,从经济、环境和社会可持续性的综合角度提供综合优化解决方案。通过提出和验证多目标决策模型来解决这一研究空白。确定了与需求相关的最佳解决方案,以平衡不同的可持续性能限制。此外,还开发了一种两阶段元启发式方法来解决该模型,其中设计了协作进化机制以同时优化拆除决策和回收率。进行了说明和验证开发的解决方案的数值实验。此外,还研究了需求对最佳决策和不同可持续绩效的影响。结果验证了我们的新模型和方法在帮助决策者找到可持续恢复的灵活路径方面的有效性,同时为分析混合恢复实施中不同需求的反作用效果提供了见解。其中合作进化机制旨在同时优化拆除决策和回收率。进行了说明和验证开发的解决方案的数值实验。此外,还研究了需求对最佳决策和不同可持续绩效的影响。结果验证了我们的新模型和方法在帮助决策者找到可持续恢复的灵活路径方面的有效性,同时为分析混合恢复实施中不同需求的反作用效果提供了见解。其中合作进化机制旨在同时优化拆除决策和回收率。进行了说明和验证开发的解决方案的数值实验。此外,还研究了需求对最佳决策和不同可持续绩效的影响。结果验证了我们的新模型和方法在帮助决策者找到可持续恢复的灵活路径方面的有效性,同时为分析混合恢复实施中不同需求的反作用效果提供了见解。研究了需求对最佳决策和不同可持续绩效的影响。结果验证了我们的新模型和方法在帮助决策者找到可持续恢复的灵活路径方面的有效性,同时为分析混合恢复实施中不同需求的反作用效果提供了见解。研究了需求对最佳决策和不同可持续绩效的影响。结果验证了我们的新模型和方法在帮助决策者找到可持续恢复的灵活路径方面的有效性,同时为分析混合恢复实施中不同需求的反作用效果提供了见解。
更新日期:2020-06-01
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