{"title":"MODELING MUNICIPAL WASTE COLLECTION USING ARTIFICIAL INTELLIGENCE TECHNIQUES","authors":"Elisabete ALBERDI CELAYA, Aitor GOTI ELORDI, Irantzu Álvarez González, Zuriñe TAPIA SANCHEZ","doi":"10.6036/10752","DOIUrl":null,"url":null,"abstract":"Even though there are numerous solutions for this process in the literature, calculating adequate vehicle routes for collecting municipal waste is still an open problem. There is still a disconnection between academics and industry professionals. The fact that academic tools are frequently difficult for actual users to operate and maintain is one of the apparent causes of this rift. The issue of municipal rubbish collection is modelled in this work utilizing a user friendly but effective—and notably straightforward—solution. The solution was based on Artificial Intelligence (AI) techniques and applied to real-world data. Three cases of different magnitudes were resolved, and in each case, a significant improvement was made. Specifically, a total theoretical reduction of 49% of the itineraries was achieved, which was partially adopted by the waste collection company as it had to consider additional restrictions.","PeriodicalId":11386,"journal":{"name":"Dyna","volume":"29 3","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dyna","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.6036/10752","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Even though there are numerous solutions for this process in the literature, calculating adequate vehicle routes for collecting municipal waste is still an open problem. There is still a disconnection between academics and industry professionals. The fact that academic tools are frequently difficult for actual users to operate and maintain is one of the apparent causes of this rift. The issue of municipal rubbish collection is modelled in this work utilizing a user friendly but effective—and notably straightforward—solution. The solution was based on Artificial Intelligence (AI) techniques and applied to real-world data. Three cases of different magnitudes were resolved, and in each case, a significant improvement was made. Specifically, a total theoretical reduction of 49% of the itineraries was achieved, which was partially adopted by the waste collection company as it had to consider additional restrictions.
期刊介绍：
Founded in 1926, DYNA is one of the journal of general engineering most influential and prestigious in the world, as it recognizes Clarivate Analytics.
Included in Science Citation Index Expanded, its impact factor is published every year in Journal Citations Reports (JCR).
It is the Official Body for Science and Technology of the Spanish Federation of Regional Associations of Engineers (FAIIE).
Scientific journal agreed with AEIM (Spanish Association of Mechanical Engineering)
In character Scientific-technical, it is the most appropriate way for communication between Multidisciplinary Engineers and for expressing their ideas and experience.
DYNA publishes 6 issues per year: January, March, May, July, September and November.
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