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.
light positioning irradiance random walk hill climbing genetic algorithms particle swarm optimization