基于机器学习的多目标位置路由优化,用于绿色城市废物管理
Yunyun Niu1, Chang Xu1, Shubing Liao1
1School of Information Engineering, China University of Geosciences, Beijing 100083, China.
Waste management (New York, N.Y.)
|April 13, 2024
概括
这项研究引入了一个新的绿色城市废物管理 (MWM) 系统,使用一个三目标位置路由问题. 该方法平衡了成本,碳排放和居民满意度,优于现有方法.
科学领域:
- 运营研究 运营研究
- 环境科学 环境科学
- 计算机科学 计算机科学
背景情况:
- 传统的城市废物管理 (MWM) 侧重于处理中心和收集路径的位置路由问题 (LRP).
- 现有的MWM系统经常忽视平衡经济成本,环境影响和居民满意度.
- 以正常分布为模型的废物需求变化增加了传统LRP的复杂性.
研究的目的:
- 开发一个绿色的MWM系统,优化总成本,碳排放和住宅满意度.
- 解决废物管理中的多目标和非决定性因素的复杂性.
- 为解决绿色MWM位置路由问题提出一个高效的算法.
主要方法:
- 建模绿色MWM系统作为一个三目标位置路由问题.
- 将废物需求纳入正常分布的独立离散随机变量.
- 开发一种利用决策树分类器指导搜索过程的多目标优化算法.
主要成果:
- 拟议的算法显示出与最先进的方法相比具有很高的竞争力.
- 实验结果验证了算法的有效性在解决复杂的MWM问题.
- 北京的一项案例研究展示了有效的位置路由策略,平衡了成本,排放和住宅满意度.
结论:
- 开发的算法有效地平衡了MWM的总成本,碳排放和住宅满意度.
- 决策树引导的优化方法提高了效率,避免了在LRP中盲目搜索.
- 这项研究为可持续,以居民为中心的城市废物管理提供了坚实的框架.
相关概念视频
Manipulation and Analysis
23
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
23
Design Example: Alignment of a Road Line Using GIS
48
The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
48
Levels of Use of a GIS
49
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
49
Selected Data About Geographic Locations
27
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
27
Applications of GIS: Disaster Management and Emergency Response
74
Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
74
Response Surface Methodology
128
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
The process of RSM involves several key steps:
128


