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NEAREST GREEDY ALGORITHM FOR SOLVING A SINGLE LANDFILL SITE SELECTION WITH RESOURCE REQUIREMENTS
NUR AZRIATI MAT1, AIDA MAUZIAH BENJAMIN2, SYARIZA ABDUL-RAHMAN3.
Landfill site selection has appeared to be an important waste management issue for future landfill planning. The selection of suitable landfill sites involves several alternative sites, along with evaluation criteria. Previously, most studies solved the landfill site selection problem by using the geographic information systems (GIS) and the multiple criteria decision making (MCDM) methods. GIS is used to identify suitable sites for a new landfill, while MCDM is used to rank the candidate sites based on the score calculated for each site. With that this paper presents a new approach that ranks the related candidate sites. These candidate sites were ranked based on several vital resource requirements, such as total travel distance to transport collected waste to the landfill, number of vehicles/ drivers required for the collection and total working hours of drivers affect the operating cost of the selected landfill. To be precise, all requirements as described above have been provided when a particular site is selected as the new landfill. These resources are identified by using the heuristic technique, namely nearest greedy. This approach was further tested on a benchmark problem set, namely waste collection vehicle routing problem with time windows. The results serve to aid the waste management team to select the most suitable location for landfill siting, besides listing the influential resource requirements for landfill site selection planning in selecting a new landfill site.
Affiliation:
- Universiti Utara Malaysia, Malaysia
- Universiti Utara Malaysia, Malaysia
- Universiti Utara Malaysia, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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4 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (0.9) |
Rank |
Q3 (Geography, Planning and Development) Q4 (Pollution) Q4 (Management, Monitoring, Policy and Law) |
Additional Information |
SJR (0.175) |
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