中文摘要：

通过分析再制造逆向物流网络模型中不确定性因素存在的原因,提出选取单位观测时间T的方法反映废旧品产生时间和地点的不确定,用模糊变量反映废旧品数量和质量的不确定,并提出基于轮盘赌的采样模糊模拟方法确定模糊数的隶属函数,使得模型能够充分利用现场信息.以投资成本和运输成本最低为目标函数建立了模糊线性规划模型,使所建模型能考虑更多的不确定因素,改变了以往模型简单假设不确定带来的问题.结合实际算例,采用混合智能算法求解,得到了优化结果,验证了模型的有效性.通过对模型中各参数进行比较分析,体现了不同机会约束中的置信水平的高低对选址策略的影响变化规律.

英文摘要：

Uncertain factors in remanufacturing reverse logistics network were analyzed. A selecting method of unit measuring time is proposed to specify the uncertainties of time and location of returned goods. Fuzzy variables were adopted to specify the uncertainties of the quantity and quality of returns. From roulette, a fuzzy sampling simulation method is developed to calculate the membership function of the fuzzy variables. The date from the nodes of network could be used in the model. A fuzzy linear programming （FLP） model is proposed based on minimizing the total cost of investment and transportation cost, which could deal with more uncertain factors than others and avoid converting uncertainties into certainty simply by assumptions. A hybrid intelligent algorithm was adopted to solve the model in a case study. The validity of the model and algorithm was demonstrated by the results. The parameters in the programming model were compared.