School of Economics and Management, Hebei University of Technology, Tianjin, P. R. China.
PLoS One. 2018 Nov 28;13(11):e0206282. doi: 10.1371/journal.pone.0206282. eCollection 2018.
Concern is growing that business enterprises focus primarily on their economic activities while disregarding the adverse environmental and social effects of these activities. To contribute to the literature on this matter, this study investigates a novel bi-objective inventory allocation planning problem with supplier selection and carbon trading across multiple periods under uncertainty. The concepts of a carbon credit price and a carbon cap are proposed to demonstrate the effect of carbon emissions costs on inventory allocation network costs. Demands of manufacturers, transport price, and defect rate of materials that should be rejected are set as random variables. We combine normalized normal constraint method, differential evolution algorithm, and uncertainty simulation to deal with the complex model. One representative case shows the effectiveness and practicability of this model and proposed method. The Pareto frontier is generated by solving the bi-objective model. We extend the results of numerical examples in large scale problems, and compare the solution method results with exact solutions. The environmental objective across the inventory allocation network varies with changes of the carbon cap and the carbon credit price.
人们越来越担心企业过于关注经济活动，而忽视了这些活动对环境和社会造成的负面影响。为了对这方面的文献做出贡献，本研究针对多周期不确定环境下的供应商选择和碳交易的新型双目标库存分配规划问题进行了研究。提出了碳信用价格和碳上限的概念，以展示碳排放成本对库存分配网络成本的影响。制造商的需求、运输价格和应拒收材料的缺陷率被设定为随机变量。我们结合归一化正态约束方法、差分进化算法和不确定性模拟来处理复杂模型。一个代表性案例展示了该模型和所提出方法的有效性和实用性。通过求解双目标模型生成帕累托前沿。我们扩展了大规模问题的数值示例结果，并将解决方案结果与精确解进行了比较。随着碳上限和碳信用价格的变化，库存分配网络的环境目标也会发生变化。
