Vehicle Routing Problem for Construction Materials
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Abstract
This research paper aimed to study outbound logistics and to design a delivery route plan for construction materials by using the algorithms for the vehicle routing problem, where products are distributed from a distribution center to several customers. The saving algorithm and genetic algorithm were applied to solve the vehicle routing problem with construction materials that were of different sizes, shapes, and weight under the available resource constraints and customer requests. The total distances and costs obtained from two algorithms were compared and the best solution was proposed. The company in Nakhon Ratchasima province in Thailand was used as a case study. Data were collected between January and December 2015 and the results showed that the generic algorithm provided a shorter distance than the current delivery system by 32.99%. Moreover, the genetic algorithm reduced the total cost of the current delivery method by 45.23%. Therefore, the solution of the generic algorithm is presented for scheduling the delivery routes for construction materials.
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References
[2] J. Masakul, “Cost reduction of goods delivery system: A case study in Malca-Amit (Thailand) Ltd.,” Bangkok: King Mongkut’s University of Technology North Bangkok, 2009 (in Thai).
[3] P. Auppatam, “The study of suitable route for waste collection: A case study of Thasala subdistrict administrative organization, Manchakiri district, Khonkean province,” M.S. thesis, Department of Civil Engineering, Faculty of Engineering, Suranaree university, 2013 (in Thai).
[4] B. Ombuki, B. J. Ross, and F. Hanshar. “Multi objective genetic algorithms for vehicle routing problem with time windows,” Applied Intelligence, vol. 21, no. 1, pp. 17–30, 2006.
[5] Y. Lin, W. Li, F. Qiu, and H. Xu, “Research on optimization of vehicle routing problem for ride-sharing taxi,” Procedia - Social and Behavioral Sciences, vol. 43, pp. 494–502, 2012.
[6] P. Flisberg, B. Lidén, and M. Rönnqvist. “A hybrid method based on linear programming and tabu search for routing of logging trucks,” Computers & Operations Research, vol. 36, no. 4, pp. 1122–1144, 2009.
[7] B. E. Gillett and L. R. Miller, “A heuristic algorithm for the vehicle dispatch problem,” Operations Research, vol. 22, pp. 340–349, 1974.
[8] P. Pongcharoen, C. Hicks, P. M. Braiden, and D. J. Stewardson, “Determining optimum genetic algorithm parameters for scheduling the manufacturing and assembly of complex products,” International Journal of Production Economics, vol. 78, no. 3, pp. 311–322, 2002.
[9] S. H Zanakis and J. R. Evans, “Heuristic optimization: why, when, and how to use it.” Interfaces. vol. 11, no. 5, pp. 84–91, 1981.
[10] B. L. Golden, T. L. Magnanti, and H. Q. Nguyen. “Implementing vehicle routing algorithms.” Networks. vol. 7, no. 2, pp. 113–148, 1977.
[11] G. Laporte, M. Gendreau, J.-Y. Potvin, and F. Semet. “Classical and modern heuristics for the vehicle routing problem,” International Transactions in Operational Research. vol. 7, no. 4–5, pp. 285–300, 2000.
[12] N. Kanchanarat, “A transportation routing system: A case study of transportating knockdown furniture,” M.S. thesis, Department of Industrial Engineering, Faculty of Engineering, Chulalongkorn University, 1999 (in Thai).
[13] K. Srimuang, “Fleet size determination in freight transportation for retail business a case study of TOPS supermarket,” M.Eng. thesis, Department of Civil Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok, 2007 (in Thai).
[14] K. Supakdee, N. Nanthasamroeng, and R. Pitakaso. “Solving a vehicle routing problem for medical equipment maintenance by saving algorithms: A case study of ubon ratchathani provincial health office,” Princess of Naradhiwas University Journal, vol. 7, pp. 23–36, 2015.
[15] T. Kangha, S. Jongruk, and P. Neammanee, “Vehicle routing of school bus using genetic algorithm,” OR-Net, pp. 49–58, 2005.
[16] A. Khadwilard, “Application of genetic algorithm for optimisation problems,” Rajamangala University of Technology Phra Nakhon Research Journal, vol. 5, no. 2, 2011 (in Thai).
[17] S. R. Thangiah, J-Y. Potvin, and T. Sun, “Heuristic approaches to vehicle routing problem with backhauls and time windows,” Computer and Operations Research, vol. 23, no. 11, pp. 1043–1057, 1996.
[18] G. Clarke and J. W. Wright, “Scheduling of vehicles from a central depot to a number of delivery points,” Operation Research. vol. 12, no. 4, pp. 568–581, 1964.
[19] J. H. Holland, Adaptation in Natural and Artificial Systems. Cambridge, MA: MIT Press., 1975.
[20] X-S. Yang, Nature-Inspired Metaheuristic Algorithms. United Kingdom, Luniver Press., 2008.
[21] M. Gen and R. Cheng, Genetic Algorithms and Engineering Optimization (Engineering Design and Automation). New York: Wiley-Interscience, 1997.
[22] W. Laoraksakiat, “A genetic algorithm for the multicompartment inventory routing problem in the distribution of the multi-type of fuel oils,” M.Eng. thesis, Department of Industrial Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok, Thailand, 2012.
