摘要
将皮革裁剪多轮廓加工空行程路径优化问题归结为广义旅行商问题,提出了一种求解问题的混合智能优化算法。用改进了的遗传模拟退火算法优化多轮廓排列序列,结合机床特征将问题转化为多段图最短路径问题,采用动态规划算法求解。对传统的Boltzmann更新准则进行改进,增加搜索记忆功能并设置双阈值,以在尽量保持最优性的前提下减少计算量;根据多段图最优子结构性质设计了个体适应度评价函数。实际应用效果和对标准问题的测试表明,新算法求解质量和收敛速度均有很大的提高。
Tool-path airtime optimization during multi-contour processing in leather cutting is regarded as generalized traveling salesman problem.A hybrid intelligence algorithm was proposed.The improved genetic simulated annealing algorithm was applied to optimize multi-contour sequence,and then combining machining characteristics,the problem was changed into multi-segment map problem which is solved with dynamic programming algorithm.Traditional Boltzmann upgrade mechanism increases memory function and sets up dual-threshold to reduce the calculation amount while maintaining the premise of optimality.Individual fitness function based on multi-segment map optimal sub-structure was designed.The practical application and the standards tests show that the algorithm has satisfactory solution quality and convergence.
出处
《计算机科学》
CSCD
北大核心
2011年第3期254-256,282,共4页
Computer Science
基金
国家自然科学基金资助项目(60970021)
浙江省重大科技专项项目(2009C11039)资助
关键词
皮革裁剪
多轮廓加工
路径优化
遗传模拟退火算法
动态规划算法
Leather cutting
Multi-contour processing
Path optimization
Genetic simulated annealing algorithm
Dynamic programming algorithm
