Supply chain optimization in automotive industry: A comparative analysis of evolutionary and swarming heuristics

Péter Veres*, Béla Illés, Christian Landschützer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


In every manufacturing, assembly or forwarder systems there are problems determined by a wide range and number of parameters. The increased number of variables and parameters leads to the increased number of required computational time for the exact solution. In this situation, heuristic and metaheuristic algorithms are useful tools to find the optimal or near optimal solutions of the problem. These methods are often combined parallel or sequencial and choosing the best algorithm is a quite complex question. There are two very important factors in computing: computational time and accuracy. In addition, there are secondary aspects, such as robustness or alternative solutions. Within the scope of this paper authors compare one of the best-known algorithms; the genetic algorithm with a relatively new swarming algorithm; the black hole algorithm. The efficiency of both algorithms will be demonstrated with a supply chain optimization problem in automotive industry, where more design tasks of logistic processes will be solved, like location and assignment of resources.

Original languageEnglish
Title of host publicationVehicle and Automotive Engineering 2
Subtitle of host publicationProceedings of the 2nd VAE2018, Miskolc, Hungary
PublisherSpringer Verlag
Number of pages11
ISBN (Print)978-3-319-75676-9
Publication statusPublished - 2018
Event2nd International Conference on Vehicle and Automotive Engineering: VAE 2018 - Miskolc, Hungary
Duration: 23 May 201825 May 2018

Publication series

NameLecture Notes in Mechanical Engineering


Conference2nd International Conference on Vehicle and Automotive Engineering
Abbreviated titleVAE 2018


  • Black hole algorithm
  • Comparison
  • Genetic algorithm
  • Warehouse positioning

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes


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