Skip to main content

Elevator group control using distributed genetic algorithm

  • Conference paper
Artificial Neural Nets and Genetic Algorithms

Abstract

In this work we have studied the applicability of genetic algorithms to the optimization of elevator group control parameters. The goal was to minimize the average passenger waiting time in a simulated office building. The elevator group control consists of a set of elevators and controllers. At the highest level of the system hierarchy the elevator group controller decides which elevator serves which call. The decision is based on the actual calls, state of the elevators (location, direction, load) and on the estimation of the traffic situation like: incoming, interfloor, outgoing, which gives some idea how the calls will be distributed within a few minutes time period. Especially in office buildings the traffic type depends on the time of the day. This allocation problem, which seems to be quite simple, turns out to be a very difficult control problem in practise and is one of the features how elevator companies can competed with one another.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. G. C. Barney and S. M. dos Santos. Elevator Traffic Analysis Design and Control. Peter Peregrinus Ltd, UK, 1985.

    Google Scholar 

  2. N.-R. Roschier and M. J. Kaakinen. New formulae for elevator round trip calculation. Supplement to Elevator World for ACUST members, pages 189–197, 1979.

    Google Scholar 

  3. M. Kaakinen and N.-R. Roeschier. Integrated elevator planning system. Elevator World, pages 73–76, March 1991.

    Google Scholar 

  4. M.-L. Siikonen. Computer modelling of elevator traffic and control. Licentiate thesis, Helsinki University of Technology, 1989. (in Finnish).

    Google Scholar 

  5. M.-L. Siikonen. Elevator traffic simulation. Simulation, pages 257–267, October 1993.

    Google Scholar 

  6. Jarmo T. Alander. An indexed bibliography of genetic algorithms: Years 1957–1993. Art of CAD Ltd., Vaasa (Finland), 1994. (over 3000 GA references).

    Google Scholar 

  7. Ricardo R. Gudwin and Fernando A. C. Gomide. Genetic algorithms and discrete event systems: an application. In Proceedings of the First IEEE Conference on Evolutionary Computation, volume 2, pages 742–745, Orlando, FL, 27.–29. June 1994. IEEE, IEEE.

    Google Scholar 

  8. P. J. Ramadge and W. M. Wonham. The control of discrete event systems. Proceedings of the IEEE, 77 (1), January 1989.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1995 Springer-Verlag/Wien

About this paper

Cite this paper

Alander, J.T., Ylinen, J., Tyni, T. (1995). Elevator group control using distributed genetic algorithm. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_104

Download citation

  • DOI: https://doi.org/10.1007/978-3-7091-7535-4_104

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-82692-8

  • Online ISBN: 978-3-7091-7535-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics