This work presents a novel automated method for optimization of luminary distribution using a simulated annealing method. The input variables of the optimization method are: luminance level, luminance uniformity, installation cost and operational cost. In addition to the development of an automated method, this work offers a graphic tool to improve the environment data input and to present the results of the luminance project. To develop an optimized project, the method requires the following information: luminary type, environment destination, environment blueprint and reflection wall conditions. In the results, we show the methodȁ9;s performance changing the simulated annealing method parameters such as initial temperature, temperature decrease rate and number of iterations at the same temperature. We also compare the results of the developed method with results presented by the lumen method and with a project developed by a specialist. In conclusion, the use of a simulated annealing optimization method for this luminance project facilitates developing an efficient tool optimizing all the parameters previously mentioned .
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