Resource planning for a single landfill site selection model based on greedy strategy: a case study

Landfilling, which has emerged as the most common method for disposal of solid waste and selection of appropriate landfill for solid waste management, is a crucial aspect in urban planning. It is compulsory to consider the various criteria, such as environmental, economic, and social criteria, in order to get the best search outcomes that can minimise the adverse effects of the surrounding population. As widely known, the process of selecting new landfills is divided into two important phases, which are: 1) the determination of potential candidate locations through an initial screening, and 2) suitability assessment based on several criteria. Previously, issues related to landfill site selection have been successfully solved by using Geographic Information System (GIS) and Multiple Criteria Decision-Making (MCDM) techniques, either individually or as an integrated approach. With that, this research aims to assist the authorities in planning a single landfill site selection by utilising all the available resources, which translates being cost-effective. Therefore, the Nearest Greedy (NG) technique had been employed to assess all five potential candidate locations by considering several related constraints. Next, the solutions were ranked based on the total distance travelled by vehicles in completing the overall waste collection process. The proposed approach was tested on a real dataset of the waste collection problem in a district located within the Northern Region of Peninsular Malaysia, which consisted of 146 residential areas and involving up to 18749 unit premises. After that, the solution obtained was compared with the present operating landfill facility, in which Candidate 4 appeared as the best alternative with a 6.74% reduction of total distance travelled, in comparison to the present operating landfill method. As such, the proposed solution may aid the local authorities and serve as a guideline in identifying suitable locations for waste disposal based on availability resources, which can discard unnecessary expenditure, such as fuel consumption.