Typical nonhierarchical coupling system multi-discipline multi-target cooperative optimization method

Abstract

The invention relates to a typical nonhierarchical coupling system multi-discipline multi-target cooperative optimization method, which comprises the following steps of: (1) decomposing a coupling system into a three-layer structure comprising a system layer, a middle layer and a discipline layer; and (2) according to the decomposed optimization problem, solving the system layer by adopting a multi-target evolutionary algorithm, solving the middle layer and the discipline layer by adopting a sequential quadratic programming algorithm, coordinating all coupling variables returned by the discipline layer in the middle layer, and returning the coordinated result to the system layer so as to realize multi-discipline multi-target optimization. A coordinator serving as the middle layer is introduced, so that the method can allow the discipline variables to be mutually overlapped. Therefore, the algorithms are more suitable for optimization design of a highly coupled nonhierarchical complex system, and the problem of multi-discipline multi-target optimization is effectively solved. The typical nonhierarchical coupling system multi-discipline multi-target cooperative optimization method can be widely applied to the field of system optimization design.

Description

A multi-disciplinary and multi-objective collaborative optimization method for typical non-hierarchical coupled systems technical field The invention relates to a system collaborative optimization method, in particular to a multidisciplinary and multi-objective collaborative optimization method for a typical non-hierarchical coupling system. Background technique With the advancement of technology and economic development, various industrial products, such as airplanes, satellites, and automobiles, have more and more functions, and the systems are becoming more and more complex, which is a typical non-hierarchical coupling system. The design and development of a complex product involves multiple disciplines, multiple departments and even multiple regions. With the improvement of cost control and efficiency requirements, the traditional serial design method can no longer meet the design requirements of contemporary complex products. Therefore, in the 1980s, research on Multi...

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Problems solved by technology

The survey found that the current multi-disciplinary and multi-objective collaborative optimization methods generally need to assume that the subject variables do not overlap, so that the points returned by subject optimization can replace the corresponding variables at the system level through simple combination, while the typical non-hierarchical coupling system between subject variables It is highly coupled, and it is difficult to achieve the case where subject variables do not overlap

If the subject variables are divided artificially to avoid overlapping between subject variables, it is equivalent to optimizing only part of the subject variables for each subject. In this way, not only the search space is reduced, but the global optimal solution may not be found, and each The reduction of the search range will inevitably reduce the convergence speed

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