Solid Waste Collection Routes Research Articles

Optimize the solid waste collection route in construction using the POA algorithm

Optimize the solid waste collection route in construction using the POA algorithm

Optimization of municipal solid waste collection routes in a Latin-American context

ABSTRACT Latin-American cities need efficient municipal solid waste (MSW) collection systems, specifically in municipalities with fast urbanization. Poor logistics in collection routes is one of the causes of inefficient MSW management. A strategy for designing the MSW collection routes, considering an environmental and economic analysis, was developed and tested in the Metropolitan Area of Monterrey (MMA), one of the cities with the highest urban and economic development in Mexico. Life cycle assessment and costs analysis were performed to evaluate archetypal routes’ environmental and economic impact in the current MSW collection system. The assessment of the environmental impact was realized through midpoint indicators of the ReCiPe 2008 method. The mathematical model describing the collection routes was developed using actual data from the MSW collection system in MMA, optimized by the Traveling Salesman Problem (TSP), and solved in RStudio. This study shows a reduction of between 9 and 20% of greenhouse gas emissions and distance covered in current collection stages, respectively. The results also demonstrate the influence of road direction, collection-truck efficiency, and traffic load in different stage on the environmental and economic impacts of the collection routes. A life cycle inventory, with realistic inputs and outputs of the MSW collection system, was developed. These inventories are scarce in Mexico and Latin America; their development helps designing cleaner MSW collection systems. Implications: The optimization of urban solid waste collection systems is a strategy to reduce costs and environmental impacts, considering factors such as distance or fuel consumption. However, mathematical models within the optimization require detailed information of the road network to achieve reliable results. In this context, Latin America shows difficulties in increasing its collection systems’ efficiency due to economic constraints and limited access to information from locals governments. The use of geographic information systems has been shown to collect real data on a city’s roads. This work aims to propose a strategy for designing urban solid waste collection routes with the least environmental and economic impacts through an optimization strategy that considers the road network’s real-time data, added to an environmental analysis developed with a life cycle assessment approach. We believe that our results could help the design of urban solid waste collection systems for cities with Latin American characteristics. Additionally, an inventory of specific inputs and emissions for waste collection in this type of city will be generated, supporting future sustainable management strategies.

Optimization of municipal solid waste collection and transportation routes, through linear programming and geographic information system: a case study from Şanlıurfa, Turkey.

Solid waste is one of the important causes of the environmental crisis that negatively impacts human health throughout the world and is fast approaching a disaster level that will pose a direct threat to human life. As with all other environmental problems, the increase in solid waste production that goes hand in hand with growing population and rising consumption has become a focus of great concern. Along with these rising levels, the investment, management and maintenance of solid waste collection and transport vehicles is seeing a continual increase in financial outlay. It is clear from the budgets of local authority solid waste management systems, 65 to 80% of which are accounted for by domestic waste, that the collection and transport of solid waste is a high-cost process and that this expenditure can be significantly reduced by the reorganisation of solid waste collection routing schedules and the minimization of collection frequency. This study demonstrates a linear programming model in order to develop an optimal routing schedule for solid waste collection and transportation, thereby reducing costs to a minimum. The neighbourhood of Veysel Karani in the Haliliye District of Şanlıurfa Province, Turkey, was specifically selected for this case study, having the suitable socio-economic and demographic variables to be representative of a metropolitan urban area. Firstly, the data regarding the municipal solid waste collection and transport routes were obtained from the local authority. Analysis and verification of these data were then performed. With the field study, these data were verified on-site, and the missing data were completed. Linear programming and geographic information system (GIS) analysis were used to determine the best route. Consequently, it is concluded that it is possible to save the route by 28% with GIS analysis and 33% with linear programming analysis according to the existing municipal solid waste collection and transportation routes.

Investigation and modelling of greenhouse gas emissions resulting from waste collection and transport activities.

Greenhouse gas emissions resulting from municipal solid waste management activities and the associated climate change impacts are getting great attention worldwide. This study investigates greenhouse gas emissions and their distribution during waste collection and transport activities in the Dammam region of Saudi Arabia. Greenhouse gas emissions and associated global warming factors were estimated based on diesel fuel consumption during waste collection and transport activities. Then, waste collection and transport data were used to parameterise a mechanistic collection model that can be used to estimate and predict future fuel consumption and greenhouse gas emissions. For the collection and transport of municipal waste in the study area, the average associated total greenhouse gas emissions were about 24,935 tCO2-eq. Global warming factors for three provinces were estimated as 25.23 kg CO2-eq t-1, 25.04 kg CO2-eq t-1, and 37.15 kg CO2-eq t-1, respectively. Lastly, the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) modelling system was used to estimate the atmospheric dispersion of greenhouse gas emissions. Model results revealed that the maximum daily greenhouse gas concentrations ranged between 0.174 and 97.3 mg m-3, while annual average greenhouse gas concentrations were found to be between 0.012 and 27.7 mg m-3 within the study domain. The highest greenhouse gas concentrations were observed for the regions involving the municipal solid waste collection routes owing to their higher source emission rates.

Solid Waste Collection Route Optimisation by Geographical Information System (GIS) in Fatih-Istanbul, Turkey

Uncontrolled urban population growth in metropolitan areas of developing countries in recent years has made solid waste management an important issue. Generally, collection and hauling efforts cover a substantial amount of total expenditures on the solid waste management by city authorities. Success of an integrated solid waste management system is directly proportional to the success of solid waste collection and transport systems since all depends on an even and a timely manner collection process. The more populated cities bring increasing difficulties on the reach and utilise services. In order to reduce cost and time on these services, it is very crucial for authorities to search for optimisation possibilities. In this manner, for local authorities, one of the most important issues on solid waste management practices is an optimised solid waste collection function. An optimised collection function has become more important in metropolitan areas having improved and sophisticated road systems. In this study, in order to minimise the route and collection cost by employing GIS and using numerical road data, a solid waste collection route optimisation study was carried in Fatih District of Istanbul, Turkey.

Proposing An Effective Route For Transporting Solid Waste Using Gis Approach

Transportation is one of the important elements in solid waste management. Effective transportation by selecting the shortest route can save time and cost in handling the waste. Thus, this paper presents a case study on deciding shortest waste transportation route from residential area to sanitary landfill in Kluang district handled by Solid Waste and Public Cleansing Management Corporation (SWCorp). The shortest transportation distance was determined using ArcGIS software on the basis of coordinate tracking, data collection for network analysis and fuel consumption estimation. The case study focuses on municipal solid waste collection routes from residential area in Kluang district to Ladang CEP 1 sanitary landfill and Seelong sanitary landfill. The study found that SWCorp could save up to 18% and 7.3% of fuel consumption per day by following the effective routes for transporting solid waste to Ladang CEP 1 sanitary landfill and to Seelong Sanitary landfill respectively. The findings could assist SWCorp saving management cost and also keep environment cleaner.

Solid Waste Collection Routes Optimization via GIS Techniques in Ipoh City, Malaysia

Waste collection becomes more complex in developing countries in terms oflogistic, fuel and labor cost and air pollutantsemission. In this study, solid waste collection routes optimizationusing Geographical Information System (GIS-ArcView) was investigated. Five routes were selected in different area of Ipoh city for pilot study and the present routes were optimized to reduce the length of the routes and consequently the time taken to complete the collection. Results indicate up to 22% length minimization in the routes. The collection duration was also reduced from 6934s to 4602 s.

Optimal solid waste collection routes identified by the ant colony system algorithm

In the present paper, the Ant Colony System (ACS) algorithm is used for the identification of optimal routes in the case of municipal solid waste (MSW) collection. The proposed MSW management system is based on a geo-referenced spatial database supported by a geographic information system (GIS). The GIS takes into account all the required parameters for solid waste collection. These parameters include static and dynamic data, such as the positions of waste bins, the road network and the related traffic, as well as the population density in the area under study. In addition, waste collection schedules, truck capacities and their characteristics are also taken into consideration. Spatio-temporal statistical analysis is used to estimate inter-relations between dynamic factors, like network traffic changes in residential and commercial areas. The user, in the proposed system, is able to define or modify all of the required dynamic factors for the creation of alternative initial scenarios. The objective of the system is to identify the most cost-effective scenario for waste collection, to estimate its running cost and to simulate its application. Finally, the results of the ACS algorithm are compared with the empirical method currently used by the Municipality of Athens.