Multi-objective Genetic Algorithm for Interior Lighting Design View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017-12-21

AUTHORS

Alice Plebe , Mario Pavone

ABSTRACT

This paper proposes a novel system to help in the design of interior lighting. It is based on multi-objective optimization of the key criteria involved in lighting design: the respect of a given target level of illuminance, uniformity of lighting, and electrical energy saving. The proposed solution integrates the 3D graphic software Blender, used to reproduce the architectural space and to simulate the effect of illumination, and the genetic algorithm NSGA-II. This solution offers advantages in design flexibility over previous related works. More... »

PAGES

222-233

Book

TITLE

Machine Learning, Optimization, and Big Data

ISBN

978-3-319-72925-1
978-3-319-72926-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-72926-8_19

DOI

http://dx.doi.org/10.1007/978-3-319-72926-8_19

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1099746626


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