The Application of Genetic Algorithm in the Assignment Problems in the Transportation Company

Open access

Abstract

The article presents the problem of the task assignment of the vehicles for the transportation company, which deals with the transport of the cargo in the full truckload system. The presented problem is a complex decision making issue which has not been analysed in the literature before. There must be passed through two stages in order to solve the task assignment problem of the vehicles for the transportation company. The first stage is to designate the tasks, the other one is to determine the number of the vehicles that perform these tasks. The task in the analysed problem is defined as transporting the cargo from the suppliers to the recipients. The transportation routes of the cargo must be determined. In order to solve the task assignment problem of the vehicles, the genetic algorithm has been developed. The construction stages of this algorithm are presented. The algorithm has been developed to solve the multi-criteria decision problem. What is more, the algorithm is verified by the use of the real input data.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • [1] Burkrd R. Dell’Amico M. Marttelo S. Assignment problems Society for Industrial and Applied Mathematics 2009.

  • [2] Ehrgott M. Multicriteria optimization Springer 2005.

  • [3] Goldberg D.E. Genetic Algorithms in Search Optimization and Machine Learning 1st Edition Addison-Wesley Professional 1989.

  • [4] Izdebski M. Jacyna-Gołda I. Wasiak M. The application of genetic algorithm for warehouse location in logistic network Journal of KONES Powertrain and Transport 23(3): 201-208 2016.

  • [5] Jacyna M. Multicriteria evaluation of traffic flow distribution in a multimodal transport corridor taking into account logistics base service Archives of Transport 11(3-4): 43-66 1999.

  • [6] Jacyna-Gołda I Izdebski M. The Multi-criteria Decision Support in Choosing the Efficient Location of Warehouses in the Logistic Network in: Procedia Engineering Elsevier BV Vol. 187 pp. 635-640 2017.

  • [7] Jacyna-Gołda I. Izdebski M. Szczepański E. Assessment of the Method Effectiveness for Choosing the Location of Warehouses in the Supply Network Challenge of Transport Telematics Springer Vol. 640 pp. 84-97 2016.

  • [8] Jacyna-Gołda I. Izdebski M. Podviezko A. Assessment of efficiency of assignment of vehicles to tasks in supply chains: A case study of a municipal company Transport Vol. 32 Iss. 3 pp. 243-251 2017.

  • [9] Lewczuk K. The concept of genetic programming in organizing internal transport processes Archives of Transport 34(2): 61-74 2015.

  • [10] Michalczewski Z. Genetic algorithms + data structure = evolutionary programs Springer 1996.

  • [11] Ombuki B. Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows Applied Intelligence Vol. 24 Iss. 1 pp. 17-30 2006.

  • [12] Pentico D. W. Assignment problems: A golden anniversary survey European Journal of Operational Research Vol. 176 Iss. 2 pp. 774-793 2007.

  • [13] Shuguang L. A hybrid population heuristic for the heterogeneous vehicle routing problems Transportation Research Part E: Logistics and Transportation Review Vol. 54 2013 pp. 67-78 2013.

  • [14] Szczepański E. Jacyna-Gołda I. Murawski J. Genetic algorithms based approach for transhipment HUB location in urban areas Archives of Transport 31(3) pp. 73-82 2014.

  • [15] Wasiak M. Jacyna-Gołda I. Transport drogowego w łańcuchach dostawWyznaczanie kosztów PWN Warszawa 2016.

Search
Journal information
Metrics
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 9 9 0
PDF Downloads 10 10 2