Municipal solid waste management is a major challenge for nowadays urban societies, because it accounts for a large proportion of public budget and, when mishandled, it can lead to environmental and social problems. This work focuses on the problem of locating waste bins in an urban area, which is considered to have a strong influence in the overall efficiency of the reverse logistic chain. This article contributes with an exact multiobjective approach to solve the waste bin location in which the optimization criteria that are considered are: the accessibility to the system (as quality of service measure), the investment cost, and the required frequency of waste removal from the bins (as a proxy of the posterior routing costs). In this approach, different methods to obtain the objectives ideal and nadir values over the Pareto front are proposed and compared. Then, a family of heuristic methods based on the PageRank algorithm is proposed which aims to optimize the accessibility to the system, the amount of collected waste and the installation cost. The experimental evaluation was performed on real-world scenarios of the cities of Montevideo, Uruguay, and Bah\'ia Blanca, Argentina. The obtained results show the competitiveness of the proposed approaches for constructing a set of candidate solutions that considers the different trade-offs between the optimization criteria.
翻译:城市固体废物管理是当今城市社会的一大挑战,因为它占公共预算的很大比例,如果处理不当,它可能导致环境和社会问题。这项工作侧重于在城市地区找到废物箱的问题,认为这对逆向物流链的总体效率具有重大影响。这一条有助于以精确的多客观的方法解决废物箱位置,其中认为最佳标准是:系统无障碍(作为服务质量衡量标准)、投资成本和从垃圾桶中清除废物所需频率(作为后游路费的替代物)。在这一方法中,提议并比较了不同方法,以在帕雷托前线实现理想和纳迪尔价值的目标。然后,提议采用一套基于PephalRank算法的超自然方法,目的是优化系统无障碍性、收集废物的数量和安装成本。实验评价是根据蒙得维的亚、乌拉圭和阿根廷Bah\'ia Blanca等城市的真实世界情景进行的。获得的结果表明,在设计不同解决方案的候选方之间,最佳贸易方法具有竞争力。