Integrating performance and parametric design tools for urban daylight enhancement

The majority of the natural lighting, in urban slums and rural areas arround the world, is blocked off and virtually no light reaches the building spaces in lower floors as well as the streets and urban spaces. Painting the buildings' surfaces may increase the availability of daylight below. Some surfaces may be easier to paint and will require less cost or effort to paint than others. This paper formulates a combinatorial optimization problem to address this situation and uses different approaches to solve the problem. The problem is solved using different optimization algorithms namely; genetic algorithms, partical swarm optimization, generalized pattern search and a hybrid approach. A comparison between the different approaches is given and recommendations on future research are made.