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Multi-objective optimization as a new approach to illumination design of interior spaces

机译：多目标优化是室内空间照明设计的新方法

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The illumination design is in general oriented towards attaining a prescribed illuminance on a work plane with the most economical lighting configuration. This work presents a new methodology to find the location and the luminous power of the light sources to satisfy a prescribed illuminance on the work plane with the constraint of lowest power consumption. Mathematically, the illumination design is inherently an inverse problem in which the boundary conditions associated to the light sources are unknown. In the proposed methodology, the inverse analysis is formulated as an optimization problem, in which the objective function aims at minimizing the total power of the light sources as well as the deviation between the prescribed and the resulting illuminance. The optimization problem is solved with the generalized extremal optimization (GEO) algorithm. The lighting calculations are based on the radiosity method. The examples discussed in the paper consider the prescription of uniform illuminance at the bottom surface of a rectangular space. The methodology leads to a set of design solutions that are capable of satisfying the problem with different levels of accuracy and energy consumption.
机译：照明设计通常旨在以最经济的照明配置在工作平面上达到规定的照明度。这项工作提出了一种新的方法，可以找到具有最低功耗约束的，满足工作平面上规定照度的光源的位置和发光功率。从数学上讲，照明设计本质上是一个逆问题，其中与光源相关的边界条件是未知的。在所提出的方法中，将反分析公式化为一个优化问题，其中目标函数旨在最小化光源的总功率以及指定照度与结果照度之间的偏差。用广义极值优化（GEO）算法解决了优化问题。照明计算基于光能传递方法。本文讨论的示例考虑了矩形空间底面上均匀照度的规定。该方法论导致了一组设计解决方案，它们能够以不同级别的精度和能耗来满足该问题。

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