Multi-objective Genetic Algorithm for Interior Lighting Design

被引：7

作者：

Plebe, Alice ^{[1
]}

Pavone, Mario ^{[1
]}

机构：

[1] Univ Catania, Dept Math & Comp Sci, Vle A Doria 6, I-95125 Catania, Italy

来源：

MACHINE LEARNING, OPTIMIZATION, AND BIG DATA, MOD 2017 | 2018年 / 10710卷

关键词：

Lighting design; Genetic algorithm; Blender; DAYLIGHTING DESIGN; OPTIMIZATION; BUILDINGS; SYSTEM;

D O I：

10.1007/978-3-319-72926-8_19

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a novel system to help in the design of interior lighting. It is based on multi-objective optimization of the key criteria involved in lighting design: the respect of a given target level of illuminance, uniformity of lighting, and electrical energy saving. The proposed solution integrates the 3D graphic software Blender, used to reproduce the architectural space and to simulate the effect of illumination, and the genetic algorithm NSGA-II. This solution offers advantages in design flexibility over previous related works.

引用

页码：222 / 233

页数：12

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