Designing cable harnesses can be time-consuming and complex due to many design and manufacturing aspects and rules. Automating the design process can help to fulfil these rules, speed up the process, and optimize the design. To accommodate this, we formulate a harness routing optimization problem to minimize cable lengths, maximize bundling by rewarding shared paths, and optimize the cables' spatial location with respect to case-specific information of the routing environment, e.g., zones to avoid. A deterministic and computationally effective cable harness routing algorithm has been developed to solve the routing problem and is used to generate a set of cable harness topology candidates and approximate the Pareto front. Our approach was tested against a stochastic and an exact solver and our routing algorithm generated objective function values better than the stochastic approach and close to the exact solver. Our algorithm was able to find solutions, some of them being proven to be near-optimal, for three industrial-sized 3D cases within reasonable time (in magnitude of seconds to minutes) and the computation times were comparable to those of the stochastic approach.

翻译：设计线束时，由于涉及众多设计制造规范与约束，过程往往耗时且复杂。自动化设计流程有助于满足这些规范、加快设计进程并优化方案。为此，我们构建了一个线束布线优化模型，目标是最小化电缆长度、通过奖励共享路径最大化线束整合度，并根据布线环境特定信息（如避让区域）优化电缆空间位置。我们开发了一种确定性强且计算高效的线束布线算法，用于求解该问题，并生成一组线束拓扑候选方案以逼近帕累托前沿。将该算法与随机求解器和精确求解器进行对比测试，结果表明：我们算法生成的目标函数值优于随机方法，且接近精确求解器。针对三个工业级三维案例，该算法能在合理时间（数秒至数分钟量级）内给出解（部分解被验证接近最优），计算耗时与随机方法相当。