A case study of heterogeneous fleet vehicle routing problem: Touristic distribution application in Alanya
Keywords:Tourism, tourist distribution, vehicle routing problem, fleet size and mix vehicle routing problem, heuristic algorithms.
In this study, Fleet Size and Mix Vehicle Routing Problem is considered in order to optimize the distribution of the tourists who have traveled between the airport and the hotels in the shortest distance by using the minimum cost. The initial solution space for the related methods are formed as a combination of Savings algorithm, Sweep algorithm and random permutation alignment. Then, two well-known solution methods named as Standard Genetic Algorithms and random search algorithms are used for changing the initial solutions. Computational power of the machine and heuristic algorithms are used instead of human experience and human intuition in order to solve the distribution problem of tourists coming to hotels in Alanya region from Antalya airport. For this case study, daily data of tourist distributions performed by an agency operating in Alanya region are considered. These distributions are then modeled as Vehicle Routing Problem to calculate the solutions for various applications. From the comparisons with the decision of a human expert, it is seen that the proposed methods produce better solutions with respect to human experience and insight. Random search method produces a solution more favorable in terms of time. As a conclusion, it is seen that, owing to the distribution plans offered by the obtained solutions, the agencies may reduce the costs by achieving savings up to 35%.
Cordeau, J. F., Laporte, G., Modelling and optimization of vehicle routing problems. In Handbook on Modelling for Discrete Optimization, Springer, 151-181 (2006).
Åžen, E., KOBÄ°'lerin UluslararasÄ± Rekabet GÃ¼Ã§lerini ArtÄ±rmada Tedarik Zinciri YÃ¶netiminin Ã–nemi. T.C. BaÅŸbakanlÄ±k DÄ±ÅŸ Ticaret MÃ¼steÅŸarlÄ±ÄŸÄ± Ä°hracatÄ± GeliÅŸtirme EtÃ¼d Merkezi, Ankara (2006).
Kocaman, S., Destinasyon YÃ¶netimi KapsamÄ±nda Marka KimliÄŸine Etki Eden FaktÃ¶rlerin Marka Ä°majÄ±na Etkisi: Alanya Ã–rneÄŸi. Akdeniz Ãœniversitesi, SBE, YayÄ±mlanmamÄ±ÅŸ Doktora Tezi, Antalya (2012).
Baldacci, R., Battarra M., Vigo, D., Routing a heterogeneous fleet of vehicles, Operations Research / Computer Science Interfaces, 43, 3-27 (2008). CrossRef
Dell'Amico, M., Monaci, M., Pagani C., Vigo, D., Heuristic approaches for the fleet size and mix vehicle routing problem with time windows. Transportation Science, 41(4), 516-526 (2007). CrossRef
Gendreau, M., Potvin, J. Y., Braysy, O., Hasle G., Lokketangen, A., Metaheuristic for the Vehicle Routing Problem and its Extensions: A Categorized Bibliography (2007). Available from: https://www.cirrelt. ca/DocumentsTravail/CIRRELT-2007-27.pdf. Accessed 15 April 2013.
Gendreau, M., Laporte, G., Musaraganyi C., Taillard, E. D., A Tabu search heuristic for the heterogeneous fleet vehicle routing problem. Computers and Operations Research, 26, 1153-1173 (1999). CrossRef
Wassan N., Osman, I., Tabu search variants for the mix fleet vehicle routing problem. Journal of the Operational Research Society. 53, 768-782 (2002). CrossRef
Choi E., Tcha, D. W., A column generation approach to the heterogeneous ï¬‚eet vehicle routing problem. Computers and Operations Research. 34, 2080â€“2095 (2007). CrossRef
Penna, P. H. V., Subramanian A., Ochi, L. S., An Iterated local search heuristic for the heterogeneous fleet vehicle routing problem. Journal of Heuristics, 19(2), 201-232 (2011). CrossRef
TÃ¼tÃ¼ncÃ¼, G. Y., An interactive GRAMPS algorithm for the heterogeneous fixed fleet vehicle routing problem with and without backhauls. European Journal of Operational Research, 201(2) 593â€“600 (2010). CrossRef
Gencer, C., KÄ±zÄ±lkaya AydoÄŸan E., Ã‡etin, S., Simultaneous pick-up and delivery decision support systems. in Decision Support Systems, Advances. Croatia, INTECH, 203-214 (2010). CrossRef
Ã‡etin, S., Ã–zkÃ¼tÃ¼k E., Gencer, C., Heterojen araÃ§ filolu eÅŸ zamanlÄ± daÄŸÄ±tÄ±m ve toplamalÄ± araÃ§ rotalama problemi iÃ§in bir karar destek sistemi. International Journal of Research and Development. 3(1) 11-18 (2011).
Ochi, L., Vianna, D., Drummond L. M., Victor, A., A Parallel evolutionary algorithm for the vehicle routing problem with heterogeneous fleet. Parallel and Distributed Processing, Lecture Notes in Computer Science, 1388, 216-224 (1998). CrossRef
Lima, C., Goldbarg, M., Goldbarg, E., A Memetic algorithm for heterogeneous fleet vehicle routing problem. Electronic Notes in Discrete Mathematics, 18, 171-176 (2004). CrossRef
Liu, S., Huang W., Ma, H., An Effective genetic algorithm for the fleet size and mix vehicle routing problems. Transportation Research Part E, 45, 434-445 (2009). CrossRef
www.alanya.com.tr, Alanya HaritasÄ±. (2012) Available from: http://www.alanya.cc/map? lang=tr&catid=hotels&itemid=77. Accessed 29 December 2012.
ALTSO, Alanya Ekonomik Rapor (2011), Alanya Ticaret ve Sanayi OdasÄ±, Alanya (2012).
Kay, M. G., Matlog: Logistics Engineering Matlab Toolbox (2013) Available from: http://www. ise. ncsu. edu/ kay/ matlog/ Accessed 16 February 2013.
TÃœÄ°K, TÃ¼rkiye Turizm Ä°statistikleri, TÃ¼rkiye Ä°statistik Kurumu, Ankara (2012).
GÃ¼leÅŸ, H. K., Paksoy, T., BÃ¼lbÃ¼l, H., Ã–zceylan, E., Tedarik Zinciri YÃ¶netimi, Gazi Kitabevi, Ankara (2010).
How to Cite
Articles published in IJOCTA are made freely available online immediately upon publication, without subscription barriers to access. All articles published in this journal are licensed under the Creative Commons Attribution 4.0 International License (click here to read the full-text legal code). This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available.
Under the Creative Commons Attribution 4.0 International License, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles in IJOCTA, so long as the original authors and source are credited.
The readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material
- for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
This work is licensed under a Creative Commons Attribution 4.0 International License.