New model and hybrid genetic algorithm for component placement of multi-head gantry mount machine

The mechanism and placement process of multi-head gantry mount machine (MHGM) is analyzed. Based on the engineering analysis, the optimization problem of placement process is decomposed to component grouping, component group pickup and component group placement problems, an integrated optimization model of MHGM is formulated, the minimum displacement of arm is objective. The component size, nozzle change and different component arrangement strategy in slots is considered. Combined with heuristic method and genetic algorithm (GA), a hybrid GA (HGA) is adopted to optimize the placement process. In the individual chromosome, the feeder index and slot index describe the arrangement sequence and position of component types in the slot. The HGA use improved order crossover, adaptive mutation and local search and contains a parallel structure. The component placement sequence and the feeder arrangement are optimized simultaneously to improve the assembly efficiency.