A typical MODO problem can be formulated as where f i( x) denotes the i-th objective function F j is the j-th constraint function is the allowable load under j-th constraint function is the equality constraint of the l-th design parameter x x u is the u-th design parameter and a u and b u are the upper and bottom boundaries of the parameter x, respectively i = 1, 2, …, m j = 1, 2, …, n u = 1, 2, …, p l = 1, 2, …, q. Therefore, to reduce the load nonuniformity and improve the system performance, it is necessary to perform the multiobjective design optimization (MODO) for the complex multicomponent system.
In addition, the multicomponent system tends to have the mutual conduction effect between components, and the design and control of one structural objective often leads to the change of another. Such multicomponent system, however, suffers from nonuniform loads caused by complex structural layout and stricter working environment, and the failure of one component will lead to the failure of the whole component system, which significantly increases the failure possibility of the multicomponent system. For example, the carrier roller system of the excavator is a typical multicomponent system. Multicomponent system is defined as the complex mechanism system comprising a plurality of rigid and flexible components, which is an indispensable part in mechanical equipment, such as excavator and loader. The comparison results demonstrate that the proposed multiobjective design optimization framework is demonstrated to hold advantages in efficiency and accuracy for multiobjective optimization.
#Nonuniform latin hypercube sampling archive#
This study then compares surrogate models (response surface model, Kriging model, OKM, and DCOKM) and optimal algorithms (neighbourhood cultivation genetic algorithm, nondominated sorting genetic algorithm, archive microgenetic algorithm, and DMOGA).
We find that the total standard deviation of three carrier rollers is reduced by 92%, where the loading distribution is more uniform after optimization. The multiobjective optimization design of the carrier roller system is considered as a study case to verify the developed approach with respect to multidirectional nonuniform loads. Furthermore, by combining DCOKM and DMOGA, the corresponding multiobjective design optimization framework for the multicomponent system is developed. To improve the accuracy and efficiency of multiobjective design optimization for a multicomponent system with complex nonuniform loads, an efficient surrogate model (the decomposed collaborative optimized Kriging model, DCOKM) and an accurate optimal algorithm (the dynamic multiobjective genetic algorithm, DMOGA) are presented in this study.
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