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Today, architectural design emphasizes high-standard buildings with sophisticated daylighting systems, because harnessing daylight provides both energy savings on lighting and psycho-physical comfort in room space. Daylighting design is a hard problem since its properties—such as lighting intensity and distribution, colors and radiant energy—vary over time. Most problem-solving techniques are forward method and are typically “trial and error ” process, attacking problems on the front end first. On the other hand, a problem-solving technique called the inverse method, which seems to be efficient, has been applied in this paper. The paper emphasizes the use of scientific-knowledge computational tools in the later stages of design in an effort to provide optimum choices of design. Genetic algorithm (GA) is used to search for optimal design strategies. A new design process has been created and implemented to increase design process efficiency. In addition to the architectural representation, this paper presents a structured method for defining and evaluating multiple objectives. Lightshelf and its daylighting system parameters are under investigation. Moreover, this work investigated several design problems, GA parameters and processes for improving design results. Results show that a new model using basic geneti