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...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2012 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/11676 |
| Acceso en línea: | http://hdl.handle.net/10256/11676 |
| Access Level: | acceso embargado |
| Palabra clave: | Programació heurística Heuristic programming Intel·ligència artificial Artificial intelligence Algorismes genètics Computer algorithms |
| Sumario: | 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 |
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