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Complexity analysis of the parallel memetic algorithm for the pickup and delivery problem with time windows

  • Silesian University of Technology

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

Abstract

Estimating the theoretical complexity of a parallel algorithm can give an impression on how it will perform in practice. However, this complexity analysis is very often omitted in the works from the parallel computation field. In this paper, we theoretically analyze the time complexity of our parallel algorithm for the pickup and delivery problem with time windows (PDPTW), which is an NP-hard discrete optimization task. The PDPTW is a hierarchical objective problem—the main objective is to minimize the number of trucks serving the transportation requests, whereas the second objective is to optimize the travel distance. In our approach, the fleet size is optimized using the parallel ejection search, and the distance is minimized using the parallel memetic algorithm. Finally, we report example experimental results showing that our parallel algorithms work very fast in practice.

Original languageEnglish
Title of host publicationMan-Machine Interactions 5 - 5th International Conference on Man-Machine Interactions, ICMMI 2017
EditorsAleksandra Gruca, Tadeusz Czachorski, Katarzyna Harezlak, Stanislaw Kozielski, Agnieszka Piotrowska, Tadeusz Czachorski
PublisherSpringer Verlag
Pages471-480
Number of pages10
ISBN (Print)9783319677910
DOIs
Publication statusPublished - 2018
Event5th International Conference on Man-Machine Interactions, ICMMI 2017 - Krakow, Poland
Duration: 3 Oct 20176 Oct 2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume659
ISSN (Print)2194-5357

Conference

Conference5th International Conference on Man-Machine Interactions, ICMMI 2017
Country/TerritoryPoland
CityKrakow
Period3/10/176/10/17

Keywords

  • Complexity analysis
  • PDPTW
  • Parallel memetic algorithm

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science

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