This article describes the application of soft computing methods for solving the problem of locating garbage accumulation points in urban scenarios. This is a relevant problem in modern smart cities, in order to reduce negative environmental and social impacts in the waste management process, and also to optimize the available budget from the city administration to install waste bins. A specific problem model is presented, which accounts for reducing the investment costs, enhance the number of citizens served by the installed bins, and the accessibility to the system. A family of single- and multi-objective heuristics based on the PageRank method and two mutiobjective evolutionary algorithms are proposed. Experimental evaluation performed on real scenarios on the cities of Montevideo (Uruguay) and Bahía Blanca (Argentina) demonstrates the effectiveness of the proposed approaches. The methods allow computing plannings with different trade-off between the problem objectives. The computed results improve over the current planning in Montevideo and provide a reasonable budget cost and quality of service for Bahía Blanca.

中文翻译：

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智慧城市垃圾堆积点多目标定位软计算方法

本文介绍了软计算方法在解决城市场景垃圾堆积点定位问题中的应用。这是现代智慧城市的一个相关问题，目的是减少废物管理过程中对环境和社会的负面影响，并优化城市管理部门用于安装垃圾箱的可用预算。提出了一个具体的问题模型，该模型说明了降低投资成本、增加安装垃圾箱服务的公民数量以及系统的可访问性。提出了一系列基于 PageRank 方法和两种多目标进化算法的单目标和多目标启发式算法。在蒙得维的亚（乌拉圭）和巴伊亚布兰卡（阿根廷）的真实场景中进行的实验评估证明了所提出方法的有效性。这些方法允许在问题目标之间进行不同权衡的计算计划。计算结果改进了蒙得维的亚的当前规划，并为 Bahía Blanca 提供了合理的预算成本和服务质量。