Organization and planning of reverse logistics networks make sustainable processes more efficient. Thus, an important sector for connecting the collection and waste paper recycling echelons is the intermediate center. In this study, a Mixed Integer Linear Programming model, which is multi-objective, multi-product, multi-level and multi-period, was developed to optimize the waste paper logistics processes of intermediate centers. The formulation includes the following echelons: collection, considering vehicle routing with different capacities; inventory of non-baling materials; baling sorted waste and inventory of bales; selling bales; disposal of non-recyclable waste. The aims of the model include: maximizing the collected waste; minimizing distances; maximizing both the production and sale of bales, and minimizing costs. According to research carried out in the literature, the developed model is a new proposal and to implement it, the Weighted Goal Programming and Revised Multi-Choice Goal Programming approaches were used to deal with multiple objectives and incorporate uncertainty into the quantity of waste available for collection. To analyze the proposed model, computational tests were executed with instances based on real data from a Brazilian company in the sector. For all performed tests, General Algebraic Modeling System 23.6.5 modeling language and CPLEX 12.2.0.2 solver were used for modeling and optimization. The results show that this study presents formulation and technological approaches that represent real situations and provide competitive solutions to the problem.

逆向物流网络的组织和规划使可持续流程更加高效。因此，连接收集和废纸回收梯队的一个重要部门是中间中心。本研究建立了多目标、多产品、多层次、多周期的混合整数线性规划模型，以优化中间中心的废纸物流流程。制定包括以下梯队：收集，考虑不同容量的车辆路线；非打包材料库存；打包分类废物和打包库存；出售大包；处理不可回收的废物。该模型的目标包括：最大化收集的废物；尽量减少距离；最大限度地提高棉包的生产和销售，并最大限度地降低成本。根据文献中进行的研究，开发的模型是一个新的建议，为了实现它，使用加权目标规划和修订的多选择目标规划方法来处理多个目标并将不确定性纳入可用于废物的数量收藏。为了分析所提出的模型，使用基于该行业一家巴西公司的真实数据的实例进行了计算测试。对于所有执行的测试，使用 General Algebraic Modeling System 23.6.5 建模语言和 CPLEX 12.2.0.2 求解器进行建模和优化。结果表明，这项研究提出了代表真实情况的配方和技术方法，并为问题提供了有竞争力的解决方案。加权目标规划和修订后的多选目标规划方法用于处理多个目标，并将不确定性纳入可供收集的废物数量。为了分析所提出的模型，使用基于该行业一家巴西公司的真实数据的实例进行了计算测试。对于所有执行的测试，使用 General Algebraic Modeling System 23.6.5 建模语言和 CPLEX 12.2.0.2 求解器进行建模和优化。结果表明，这项研究提出了代表真实情况的配方和技术方法，并为问题提供了有竞争力的解决方案。加权目标规划和修订后的多选目标规划方法用于处理多个目标，并将不确定性纳入可供收集的废物数量。为了分析所提出的模型，使用基于该行业一家巴西公司的真实数据的实例进行了计算测试。对于所有执行的测试，使用 General Algebraic Modeling System 23.6.5 建模语言和 CPLEX 12.2.0.2 求解器进行建模和优化。结果表明，这项研究提出了代表真实情况的配方和技术方法，并为问题提供了有竞争力的解决方案。