| Title: | A multi-objective solution of green vehicle routing problem |
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| Authors: | ID Kabadurmuş, Özgür (Author)
ID Erdoğan, Mehmet Serdar (Author)
ID Özkan, Yiğitcan (Author)
ID Köseoğlu, Mertcan (Author) |
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| Files: |  RAZ_Kabadurmuş_Ozgur_2019.pdf (764,60 KB)
MD5: 9B09DDB0FEDAA45FE3B11789C5151132
 https://doi.org/10.2478/jlst-2019-0003
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| Language: | Slovenian |
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| Work type: | Unknown |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FL - Faculty of Logistic
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| Abstract: | Distribution is one of the major sources of carbon emissions and this issue has been addressed by Green Vehicle Routing Problem (GVRP). This problem aims to fulfill the demand of a set of customers using a homogeneous fleet of Alternative Fuel Vehicles (AFV) originating from a single depot. The problem also includes a set of Alternative Fuel Stations (AFS) that can serve the AFVs. Since AFVs started to operate very recently, Alternative Fuel Stations servicing them are very few. Therefore, the driving span of the AFVs is very limited. This makes the routing decisions of AFVs more difficult. In this study, we formulated a multi-objective optimization model of Green Vehicle Routing Problem with two conflicting objective functions. While the first objective of our GVRP formulation aims to minimize total CO2 emission, which is proportional to the distance, the second aims to minimize the maximum traveling time of all routes. To solve this multi-objective problem, we used �-constraint method, a multi-objective optimization technique, and found the Pareto optimal solutions. The problem is formulated as a Mixed-Integer Linear Programming (MILP) model in IBM OPL CPLEX. To test our proposed method, we generated two hypothetical but realistic distribution cases in Izmir, Turkey. The first case study focuses on an inner-city distribution in Izmir, and the second case study involves a regional distribution in the Aegean Region of Turkey. We presented the Pareto optimal solutions and showed that there is a tradeoff between the maximum distribution time and carbon emissions. The results showed that routes become shorter, the number of generated routes (and therefore, vehicles) increases and vehicles visit a lower number of fuel stations as the maximum traveling time decreases. We also showed that as maximum traveling time decreases, the solution time significantly decreases. |
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| Keywords: | green vehicle routing problem, alternative fuel vehicles, epsilon-constraint, multi-objective optimization, Pareto optimality |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 28.06.2019 |
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| Year of publishing: | 2019 |
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| Number of pages: | 31-44 |
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| Numbering: | Letn. 10, št. 1 |
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| PID: | 20.500.12556/DKUM-90093  |
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| UDC: | 502.12:629 |
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| ISSN on article: | 2232-4968 |
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| COBISS.SI-ID: | 130215171 |
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| DOI: | 10.2478/jlst-2019-0003 |
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| Publication date in DKUM: | 22.08.2024 |
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| Views: | 191 |
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| Downloads: | 12 |
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| Metadata: |    |
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| Categories: | Misc.
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