Abstract
Current studies on cable harness layouts have mainly focused on cable harness route planning. However, the topological structure of a cable harness is also extremely complex, and the branch structure of the cable harness can affect the route of the cable harness layout. The topological structure design of the cable harness is a key to such a layout. In this paper, a novel multi-branch cable harness layout design method is presented, which unites the probabilistic roadmap method (PRM) and the genetic algorithm. First, the engineering constraints of the cable harness layout are presented. An obstacle-based PRM used to construct non-interference and near to the surface roadmap is then described. In addition, a new genetic algorithm is proposed, and the algorithm structure of which is redesigned. In addition, the operation probability formula related to fitness is proposed to promote the efficiency of the branch structure design of the cable harness. A prototype system of a cable harness layout design was developed based on the method described in this study, and the method is applied to two scenarios to verify that a quality cable harness layout can be efficiently obtained using the proposed method. In summary, the cable harness layout design method described in this study can be used to quickly design a reasonable topological structure of a cable harness and to search for the corresponding routes of such a harness.
Highlights
Cable harnesses are widely used in complex mechatronics products as the transmission medium of power and digital signals
To design the topological structure of the cable harness with many branch points, we present a multi-branch cable harness layout method by uniting the probabilistic roadmap method (PRM) with the genetic algorithm (GA)
This paper provides the details of the GA for a branch structure design and branch point determination
Summary
Cable harnesses are widely used in complex mechatronics products as the transmission medium of power and digital signals. Wang et al [14] presented a cable harness layout method based on a multi-scale chaotic mutation particle swarm optimization algorithm. Wu et al [15] presented a path-planning method for the cable harness layout based on an improved ant colony optimization algorithm. The current methods supplied different solutions for the cable harness layout, they focused on the route searching problem or the branch point searching problem of the cable harness layout design. To design the topological structure of the cable harness with many branch points, we present a multi-branch cable harness layout method by uniting the PRM with the GA. The third operation is as follows: if the branch points of an individual decrease, the endpoint connected to the Population Initialization. The K branch points are randomly selected, and the endpoint and other branch points that the selected branch points are connected with are changed
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