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Energy-saving light positioning using heuristic search

A new definition is given to the problem of light positioning in a closed environment, aiming at obtaining, for a global illumination radiosity solution, the position and emission power for a given number of lights that provide a desired illumination at a minimum total emission power. Such a desired illumination is expressed using minimum and/or maximum values of irradiance allowed, resulting in a combinatory optimization problem. A pre-process computes and stores irradiances for a pre-established set of light positions by means of a radiosity random walk. The reuse of photon paths makes this pre-process reasonably cheap. Different heuristic search algorithms, combined to linear programming, are discussed and compared, from the simplest hill climbing strategies to the more sophisticated population-based and hybrid approaches. The paper shows how the presented approaches make it possible to obtain a good solution to the problem at a reasonable cost

This project has been funded in part with grant number TIN2010-21089-C03-01 from Spanish Government, and with grant number 2009 SGR 643 from Catalan Government

© Engineering Applications of Artificial Intelligence, 2012, vol. 25, núm.3, p. 566-582

Elsevier

Author: Castro Villegas, Francesc
Acebo Peña, Esteve del
Sbert, Mateu
Date: 2012
Abstract: A new definition is given to the problem of light positioning in a closed environment, aiming at obtaining, for a global illumination radiosity solution, the position and emission power for a given number of lights that provide a desired illumination at a minimum total emission power. Such a desired illumination is expressed using minimum and/or maximum values of irradiance allowed, resulting in a combinatory optimization problem. A pre-process computes and stores irradiances for a pre-established set of light positions by means of a radiosity random walk. The reuse of photon paths makes this pre-process reasonably cheap. Different heuristic search algorithms, combined to linear programming, are discussed and compared, from the simplest hill climbing strategies to the more sophisticated population-based and hybrid approaches. The paper shows how the presented approaches make it possible to obtain a good solution to the problem at a reasonable cost
This project has been funded in part with grant number TIN2010-21089-C03-01 from Spanish Government, and with grant number 2009 SGR 643 from Catalan Government
Format: application/pdf
ISSN: 0952-1976
0952-1976
Document access: http://hdl.handle.net/10256/11676
Language: eng
Publisher: Elsevier
Collection: MICINN/PN 2011-2013/TIN2010-21089-C03-01
AGAUR/2009-2014/2009 SGR-643
Reproducció digital del document publicat a: http://dx.doi.org/10.1016/j.engappai.2011.11.009
Articles publicats (D-IMA)
Is part of: © Engineering Applications of Artificial Intelligence, 2012, vol. 25, núm.3, p. 566-582
Rights: Tots els drets reservats
Subject: Programació heurística
Heuristic programming
Intel·ligència artificial
Artificial intelligence
Algorismes genètics
Computer algorithms
Title: Energy-saving light positioning using heuristic search
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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