Building a Decision Support System for Vehicle Routing Problem: A Real-Life Case Study from Turkey

dc.contributor.author Ayşenur Doğan
dc.contributor.author İrem Bilici
dc.contributor.author Osman Kaan Demiral
dc.contributor.author Mehmet Serdar Erdoğan
dc.contributor.author Ozgur Kabadurmus
dc.contributor.author Doğan, Ayşenur
dc.contributor.author Demiral, Osman Kaan
dc.contributor.author Erdoğan, Mehmet Serdar
dc.contributor.author Bilici, İrem
dc.contributor.author Kabadurmuş, Özgür
dc.contributor.editor M.N. Osman Zahid , R. Abd. Aziz , A.R. Yusoff , N. Mat Yahya , F. Abdul Aziz , M. Yazid Abu , N.M. Durakbasa , M.G. Gençyilmaz
dc.date.accessioned 2025-10-06T17:51:10Z
dc.date.issued 2020
dc.description.abstract One of the most costly operations in logistics is the distribution of goods. Inefficient vehicle routes increase distribution costs especially for companies performing distribution operations daily. Vehicle Routing Problem (VRP) addresses this inefficiency and optimizes the distribution routes of vehicles. In this study we developed a decision support system to solve the Vehicle Routing Problem with Time Windows and Split Delivery and applied it to a real-life case company. The data of the problem were obtained by a real logistic company which is one of the leading Turkish logistics companies located in Izmir Turkey. The company distributes goods to the customers located in various cities in Turkey and currently does not use any decision-making tool to optimize the routes of its trucks. We formulated the mathematical model as Mixed Integer Linear Programming (MILP) and solved it by using IBM OPL CPLEX. Our proposed decision support system clusters the customers into geographical groups and then optimizes the routes within the clusters. The results of the decision support system can be manually adjusted by the decision maker to fine-tune the routes. We demonstrated the efficiency of our proposed methodology on the regional distribution of the company. The results of the study showed that our proposed model decreases the total distribution distance by 16% and total distribution time by approximately 13%. © 2022 Elsevier B.V. All rights reserved.
dc.description.sponsorship Yasar University
dc.description.sponsorship Burak Can Özaslan, Nazmihan Öterbülbül and Emre Can Kayadelen also helped this study during their senior design project at Yasar University in 2019.
dc.identifier.doi 10.1007/978-3-030-31343-2_57
dc.identifier.isbn 9789819650583, 9783031991585, 9783031948886, 9789819667314, 9789811937156, 9783030703318, 9789811622779, 9789811969447, 9789819701056, 9789819748051
dc.identifier.isbn 9789811509490
dc.identifier.isbn 9783030313425
dc.identifier.issn 21954364, 21954356
dc.identifier.issn 2195-4356
dc.identifier.scopus 2-s2.0-85076227398
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076227398&doi=10.1007%2F978-3-030-31343-2_57&partnerID=40&md5=ff6dc187e96c8618028ae08d931396ff
dc.identifier.uri https://gcris.yasar.edu.tr/handle/123456789/9315
dc.identifier.uri https://doi.org/10.1007/978-3-030-31343-2_57
dc.language.iso English
dc.publisher Springer Science and Business Media Deutschland GmbH
dc.relation.ispartof 19th International Symposium for Production Research ISPR 2019
dc.rights info:eu-repo/semantics/closedAccess
dc.source Lecture Notes in Mechanical Engineering
dc.subject Heterogeneous Fleet, Mixed Integer Linear Programming Model, Optimization, Time Windows, Vehicle Routing Problem, Artificial Intelligence, Decision Making, Distribution Of Goods, Fleet Operations, Integer Programming, Vehicle Routing, Vehicles, Case-studies, Distribution Costs, Distribution Operations, Heterogeneous Fleet, Life Case, Logistics Company, Mixed Integer Linear Programming Model, Optimisations, Time Windows, Vehicle Routing Problems, Decision Support Systems
dc.subject Artificial intelligence, Decision making, Distribution of goods, Fleet operations, Integer programming, Vehicle routing, Vehicles, Case-studies, Distribution costs, Distribution operations, Heterogeneous fleet, Life case, Logistics company, Mixed integer linear programming model, Optimisations, Time windows, Vehicle Routing Problems, Decision support systems
dc.subject Vehicle Routing Problem
dc.subject Mixed Integer Linear Programming Model
dc.subject Optimization
dc.subject Time Windows
dc.subject Heterogeneous Fleet
dc.title Building a Decision Support System for Vehicle Routing Problem: A Real-Life Case Study from Turkey
dc.type Conference Object
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gdc.description.departmenttemp [Doğan A.] International Logistics Management, Yasar University, Izmir, Turkey; [Bilici İ.] International Logistics Management, Yasar University, Izmir, Turkey; [Demiral O.K.] International Logistics Management, Yasar University, Izmir, Turkey; [Erdoğan M.S.] International Logistics Management, Yasar University, Izmir, Turkey; [Kabadurmuş Ö.] International Logistics Management, Yasar University, Izmir, Turkey
gdc.description.endpage 675
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
gdc.description.startpage 661
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gdc.virtual.author Erdoğan, Mehmet Serdar
gdc.virtual.author Kabadurmuş, Özgür
oaire.citation.endPage 675
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person.identifier.scopus-author-id Doğan- Ayşenur (57212208522), Bilici- İrem (57212208209), Demiral- Osman Kaan (57212215257), Erdoğan- Mehmet Serdar (57195507610), Kabadurmus- Ozgur (24604956200)
project.funder.name Burak Can Özaslan Nazmihan Öterbülbül and Emre Can Kayadelen also helped this study during their senior design project at Yasar University in 2019.
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