Crane Telescopic Boom Optimization Based on Real-Coded Genetic Algorithm

The traditional optimization methods for the crane telescopic boom have some shortages and genetic algorithm is a novel and powerful method for mechanical optimization design. The space of chromosomes with real-coded genetic algorithm (RCGA) and the problem solution space are the same space, the problems of solution precision and redundant codes in binary-coded genetic algorithm (BCGA) are solved with RCGA; Operators are modified as appropriate one; Engineering domain knowledge could be naturally integrated with RCGA, and the legacy codes of the traditional algorithms can be reused with RCGA for coding. So BCGA is more suitable to solve complex engineering design optimization problems with continuing variants. The optimization model with penalty function for crane telescopic boom is very suitable for the physical problem. This design method can effectively reduce the boom weight and improve the forces exerted on it. Result shows that RCGA has practical application in engineering design.