Optimization of constructional layout by improved genetic and memetic algorithms

Baušys, Romualdas; Pankrašovaitė, Ina

Use this url to cite publication: https://hdl.handle.net/20.500.14911/118670

Optimization of constructional layout by improved genetic and memetic algorithms

Details

Publication Type (CRIS)

Straipsnis konferencijos medžiagoje Web of Science duomenų bazėje / Article in conference proceedings in Web of Science database (P1a1)

Publication Type (eLABa)

Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB (P1a)

Author(s)

Author	Affiliation
Baušys, Romualdas	Grafinių sistemų katedra / Department of Graphical Systems (1048)
Pankrašovaitė, Ina	Grafinių sistemų katedra / Department of Graphical Systems (1048)

Title

Optimization of constructional layout by improved genetic and memetic algorithms

[en]

R. Baušys, Ina Pankrašovaitė

Is part of

The 9th international conference Modern building materials, structures and techniques: selected papers, May 16-18, 2007 Vilnius, Lithuania / International Association for Bridges and Structural Engineering, European Council of Civil Engineers, The Association of European Civil Engineering Faculties, Lithuanian Academy of Science, Vilnius Gediminas Technical University. Vol. 3

Published In

Year	Start Page	End Page
2007	904	909

Publisher

Vilnius : Technika, 2007

Referenced in Database(s)(DBs)

ISI Proceedings

Extent

p. 904-909

URI

URI
https://hdl.handle.net/20.500.14911/118670

Cited references

Science / Art Area

Technologijos mokslai / Technological sciences (T)

Field of Science / Art

Mechanikos inžinerija / Mechanical Engineering (T009)

Keywords (en)

Abstract (en)

In this paper we consider constructional layout problem that seeks to determine the layout of Units based on lighting, heating, available sizes and other objectives and constraints. For design of constructional layout we present an approach based on evolutionary search method known as the genetic algorithms (GAs). However, the rate of convergence of GAs is often not good enough at their current stage. For this reason, the improved genetic algorithm and memetic algorithm are proposed. We have analyzed and compared the performance of standard genetic algorithm, improved genetic algorithm and memetic algorithm for constructional layout problem solutions and presented the results of performance.