Collection and transportation of solid waste are costly for municipal budgets. This study challenges the use of existing administrative boundaries in waste management applications. By reducing the spread (standard deviation) of parameters (landfills, populated places, and roads), efficient and practical waste management regions are created. A novel alteration to the Centroidal Voronoi Tessellation (CVT) algorithm is proposed where Thiessen polygons are created using the central feature of a subset of data instead of the geometric centroid. The results applying the central feature method are compared to traditional CVT methods. Two Canadian provinces (Saskatchewan and Nova Scotia), the City of Regina, and two New York City boroughs (Manhattan and the Bronx) are investigated. Results suggest that the newly proposed tool can reduce the standard deviation of selected parameters compared to CVT. The spatial distribution of data and the geometry of the input tessellations are important factors in optimization. In Saskatchewan, reductions in parameter standard deviations ranged between 7.0 and 23.8% when comparing the two methods. In Nova Scotia, reductions in standard deviation of 9.64–13.25% were observed. In the City of Regina, wards may be more effective in planning solid waste collection compared to current solid waste collection boundaries. The standard deviation of parameters was minimized by 32.2–55.0% in New York. The proposed method may be able to efficiently create waste management regions in both cities and provinces, helping to reduce waste collection and transportation costs by ensuring an even spread of parameters in each region.

固体废物的收集和运输对于市政预算来说是昂贵的。这项研究对废物管理应用中现有管理界限的使用提出了挑战。通过减少参数（垃圾填埋场，人口稠密的地方和道路）的传播（标准偏差），可以创建有效而实用的废物管理区域。提出了一种对质心Voronoi细分（CVT）算法的新颖更改，其中使用数据子集的中心特征而不是几何质心创建了Thiessen多边形。将采用中心特征方法的结果与传统的CVT方法进行了比较。调查了两个加拿大省（萨斯喀彻温省和新斯科舍省），里贾纳市和两个纽约市行政区（曼哈顿和布朗克斯区）。结果表明，与CVT相比，新提出的工具可以减少所选参数的标准偏差。数据的空间分布和输入镶嵌的几何形状是优化的重要因素。在萨斯喀彻温省，比较这两种方法时，参数标准偏差的减少范围为7.0至23.8％。在新斯科舍省，观察到标准偏差降低了9.64–13.25％。与当前的固体废物收集边界相比，在里贾纳市，病房可能更有效地计划固体废物收集。在纽约，参数的标准偏差最小化了32.2-55.0％。所提出的方法可能能够有效地在城市和省份中创建废物管理区域，