Optimum spacing design of grillage systems using a genetic algorithm
Advances in Engineering Software
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Parameter optimization for growth model of greenhouse crop using genetic algorithms
Applied Soft Computing
Heuristic-Search-Based Light Positioning According to Irradiance Intervals
SG '09 Proceedings of the 10th International Symposium on Smart Graphics
Energy-saving light positioning using heuristic search
Engineering Applications of Artificial Intelligence
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A genetic algorithm technique is developed for the optimal design of a supplemental lighting system for greenhouse crop production. The approach uses the evolutionary parallel search capabilities of genetic algorithms to design the pattern layout of the lamps (luminaires), their mounting heights and their wattages. The total number and the exact positions of luminaires are not predefined (even though possible positions lay on a fixed grid layout), thus the genetic algorithm system has a large degree of freedom in the designing process. The possibilities of mounting heights and luminaire wattages are limited to four different values for each luminaire in this study. A fitness function for the genetic algorithm was developed, taking into account light uniformity, light intensity capability, shading effects of the design, as well as operational and investment costs. The systems designed by the genetic algorithm show improved values of light uniformity and substantial savings without any effect on the light capacity capabilities of the system. Innovative automatically designed systems compare favorably with typical and expert-designed lighting systems.