基于优化蚁群算法的电缆敷设路径规划

针对基于传统手工设计的电缆敷设存在误差大和效率低等问题,将蚁群算法优化的计算机辅助设计应用到电缆敷设路径规划中.利用蚁群算法在复杂线路中多端点的线路计算优势,解决电缆敷设的最短路径问题.同时,本文将电缆敷设路径平面化,进一步利用Gompertz函数从信息素限定和挥发因子自适应调整两方面进行优化,提高了蚁群算法的收敛速度和全局性.仿真实验表明,优化的蚁群算法在变电站数字化三维电缆敷设过程能够快速得出最短电缆敷设路径,节省人力物资成本,提高了设计精度.

Cable laying path planning based on optimized ant colony algorithm

To address the large error and low efficiency of traditional manual design in cable laying task,the computer-aided design optimized by Ant Colony Algorithm (ACA) is applied to cable laying path planning.The shortest path for cable laying is solved via the ACA''s multi terminal path calculation for complex path planning.Furthermore,the planarized cable laying path is optimized via Gompertz function in aspects of pheromone restriction and self-adaptive adjustment of volatilization factor,thus improves the ACA in both convergence speed and global performance.The simulation results show that the optimized ant colony algorithm can quickly obtain the shortest cable laying path in the task of substation digital 3D cable laying,which saves the cost of manpower and materials,and improves the design accuracy.