Arc Routing Problem Approach for Reducing Exhaust Gas Emission in Road Transportation: A Case Study of Erzurum

dc.contributor.author Codur, Merve Kayaci
dc.contributor.author Yilmaz, Mustafa
dc.contributor.author Codur, Muhammed Yasin
dc.date.accessioned 2026-03-26T15:30:01Z
dc.date.available 2026-03-26T15:30:01Z
dc.date.issued 2019
dc.description Çodur, Muhammed Yasin/0000-0001-7647-2424 en_US
dc.description.abstract One of the sectors that have the greatest impact on greenhouse gas emissions around the world is the road transportation sector. For this reason, the studies carried out for the logistic activities of the enterprises and entrepreneurs in a way that will cause the least harm to the environment are accelerating day by day. Some processes are routinely carried out on the road to ensure both transportation safety and environmental regulation. One of these processes is the snow plowing process, which is frequently performed in winter months. There are several heavy-duty vehicles that using for snow plowing operations on the roads, and these vehicles are seriously releasing exhaust gases. Therefore, in this study, the measures reducing the adverse effects of exhaust emissions on the environment arising from road vehicles were analyzed by arc routing problem approach. As one of these measures, transportation planning of the vehicles traveling on the road network and the completion of the process by vehicles in the shortest distance is expected. The optimum routes of vehicles traveling on the roads are critically important in terms of cost, distance and environmental effects. In this study, multiple vehicle variants of k-Chinese Postman Problem (k-CPP), which is one of the most frequently used approaches of arc routing problems, are addressed. A new type called Balanced k-Chinese Postman Problem (Bk-CPP) that balances the workload among vehicles and that has an important role for real-world applications is developed. A bi-objective integer-programming model is presented. There are two objectives; to minimize the total distance covered, and to balance the workload in terms of distance traveled among vehicles as much as possible. The proposed Bk-CPP model is applied to a network of a part of Ataturk University campus in Turkey for snow plowing operations. Additionally, well-known arc routing test instances that are widely used in the literature are solved to demonstrate the effectiveness and applicability of the proposed Bk-CPP model. The results show that the optimum routes significantly outperform to reduce the amount of exhaust gas emissions. en_US
dc.identifier.issn 1018-4619
dc.identifier.issn 1610-2304
dc.identifier.scopus 2-s2.0-85073457980
dc.identifier.uri https://hdl.handle.net/20.500.14901/4700
dc.language.iso en en_US
dc.publisher Parlar Scientific Publications (p S P) en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Arc Routing en_US
dc.subject Chinese Postman Problem en_US
dc.subject CO2 Emissions en_US
dc.subject Transportation Network Modeling en_US
dc.subject Transportation Planning en_US
dc.title Arc Routing Problem Approach for Reducing Exhaust Gas Emission in Road Transportation: A Case Study of Erzurum en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Çodur, Muhammed Yasin/0000-0001-7647-2424
gdc.author.scopusid 57194165624
gdc.author.scopusid 58587171500
gdc.author.scopusid 29667475400
gdc.author.wosid Kayaci Çodur, Merve/Jmg-8728-2023
gdc.author.wosid Yilmaz, Mustafa/Aae-4022-2020
gdc.author.wosid Çodur, Muhammed Yasin/A-6290-2013
gdc.description.department Erzurum Technical University en_US
gdc.description.departmenttemp [Codur, Merve Kayaci; Yilmaz, Mustafa] Ataturk Univ, Ind Engn Dept, TR-25200 Erzurum, Turkey; [Codur, Muhammed Yasin] Erzurum Tech Univ, Civil Engn Dept, Erzurum, Turkey en_US
gdc.description.endpage 7205 en_US
gdc.description.issue 10 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 7196 en_US
gdc.description.volume 28 en_US
gdc.description.woscitationindex Science Citation Index Expanded - Social Science Citation Index
gdc.description.wosquality N/A
gdc.identifier.wos WOS:000487347700022

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