基于改进遗传算法的岛礁区航路规划模型
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摘要
为解决船舶穿过岛礁区时危险度大、航行难、航路规划复杂等问题,提出应用实数路径点编码配合采取精英保留策略的遗传算法。考虑船舶的转向困难性、航程、人为指定经过路径点以及船舶安全性,建立适应度函数评价模型。在电子海图平台上提取障碍物特征多边形顶点坐标,规划出最佳航路。该算法能解决多约束条件下的多目标优化问题。对舟山岛礁区进行实例验证。结果表明,改进后的遗传算法能够解决岛礁区的复杂航路规划问题,且实现简单,收敛速度较快,也不易陷入局部极小值。随着自动控制技术的不断发展,可为船舶在岛礁区的自主航行提供理论支持。
In order to solve the problems of high risk,difficult navigation and complicated route planning for ships through the island and reef areas,a genetic algorithm is proposed using the real path point coding and the elite reservation strategy. Considering the ship steering difficulty,sailing range,designated path points and ship safety,the fitness function evaluation model is established. Based on the electronic chart system,vertex coordinates of characteristic polygons of obstacles are extracted,and the optimal path is planned. The algorithm can solve the multi-objective optimization issues under multi-constraints. The Zhoushan island and reef area are taken for example. The results show that,the improved genetic algorithm is feasible for the complicated route planning problem of island and reef areas,is of easy implementation and faster convergence,and is not easy to be lost into the local minimum. With the development of automatic control technology,it can provide theoretical support for the autonomous navigation of ships through the island and reef areas.
In order to solve the problems of high risk,difficult navigation and complicated route planning for ships through the island and reef areas,a genetic algorithm is proposed using the real path point coding and the elite reservation strategy. Considering the ship steering difficulty,sailing range,designated path points and ship safety,the fitness function evaluation model is established. Based on the electronic chart system,vertex coordinates of characteristic polygons of obstacles are extracted,and the optimal path is planned. The algorithm can solve the multi-objective optimization issues under multi-constraints. The Zhoushan island and reef area are taken for example. The results show that,the improved genetic algorithm is feasible for the complicated route planning problem of island and reef areas,is of easy implementation and faster convergence,and is not easy to be lost into the local minimum. With the development of automatic control technology,it can provide theoretical support for the autonomous navigation of ships through the island and reef areas.
引文
[1]熊海生.岛礁区通航环境安全评估研究[D].大连:大连海事大学,2014.
[2]孙树栋,曲彦宾.遗传算法在机器人路径规划中的应用研究[J].西北工业大学学报,1998,16(1):79-83.
[3]SUGIHARA K,SMITH J.Genetic algorithms for adaptive motion planning of an autonomous mobile robot[C]//IEEE International Symposium on Computational Intelligence in Robotics and Automation,1997.Proceedings IEEE,1997:138-143.https://doi.org/10.1109/cira.1997.613850.
[4]周明,孙树栋,彭炎午.使用遗传算法规划移动机器人路径[J].西北工业大学学报,1998,16(4):580-583.
[5]周明,孙树栋,彭炎午.基于遗传模拟退火算法的机器人路径规划[J].航空学报,1998,19(1):118-120.DOI:10.3321/j.issn:1000-6893.1998.01.026.
[6]安柏义,曹云峰.基于动态规划的无人机航路优化问题研究[J].计算机测量与控制,2008,16(8):1177-1179,1194.DOI:10.16526/j.cnki.11-4762/tp.2008.08.002.
[7]穆晓敏,姜智超,包一鸣,等.低空突防最优航路规划算法与仿真[J].航天控制,2005,23(1):45-50.DOI:10.3969/j.issn.1006-3242.2005.01.011.
[8]汪柱,李树军,张立华,等.基于航路二叉树的航线自动生成方法[J].武汉大学学报(信息科学版),2010,35(4):407-410.DOI:10.13203/j.whugis2010.04.015.
[9]王莹,刘维亭.基于改进蚁群算法的舰船航路规划研究[J].现代电子技术,2010,33(21):186-188,196.DOI:10.16652/j.issn.1004-373x.2010.21.014.
[10]邹春明,赵俊超,杨柯,等.基于惩罚-PSO的群桥水域多约束航路规划[J].中国航海,2016,39(2):67-70.DOI:10.3969/j.issn.1000-4653.2016.02.016.
[11]刘俊丽,韩旭.遗传算法技术浅论[J].电脑学习,2009(5):142-143.DOI:10.3969/j.issn.2095-2163.2009.05.070.
[12]徐建国.岛礁区航行方法与应急措施[J].中国水运,1997(8):29-30.DOI:10.13646/j.cnki.42-1395/u.1997.08.015.
[13]吕呼平.浅谈大型船舶在舟山岛礁区航行的方法[C]//中国航海学会优秀论文文摘及学术会议论文目次汇编(1990-1991).上海,1992:2.
[14]张云鹏,张吉平.大型船舶沿岸航行富余水深的研究[J].大连海事大学学报,2014,40(3):33-36.DOI:10.16411/j.cnki.issn1006-7736.2014.03.017.
[15]栾法敏.沿岸通航密集区航行风险识别、评估和控制[J].中国航海,2014,37(3):80-84.DOI:10.3969/j.issn.1000-4653.2014.03.019.
[16]张锡海.曹妃甸港及其附近水域航路优化的研究[D].大连:大连海事大学,2007.DOI:10.7666/d.y1037209.
[17]马全党.典型水域船舶航路动态规划模型及其应用研究[D].武汉:武汉理工大学,2012.DOI:10.7666/d.y2099337.
[2]孙树栋,曲彦宾.遗传算法在机器人路径规划中的应用研究[J].西北工业大学学报,1998,16(1):79-83.
[3]SUGIHARA K,SMITH J.Genetic algorithms for adaptive motion planning of an autonomous mobile robot[C]//IEEE International Symposium on Computational Intelligence in Robotics and Automation,1997.Proceedings IEEE,1997:138-143.https://doi.org/10.1109/cira.1997.613850.
[4]周明,孙树栋,彭炎午.使用遗传算法规划移动机器人路径[J].西北工业大学学报,1998,16(4):580-583.
[5]周明,孙树栋,彭炎午.基于遗传模拟退火算法的机器人路径规划[J].航空学报,1998,19(1):118-120.DOI:10.3321/j.issn:1000-6893.1998.01.026.
[6]安柏义,曹云峰.基于动态规划的无人机航路优化问题研究[J].计算机测量与控制,2008,16(8):1177-1179,1194.DOI:10.16526/j.cnki.11-4762/tp.2008.08.002.
[7]穆晓敏,姜智超,包一鸣,等.低空突防最优航路规划算法与仿真[J].航天控制,2005,23(1):45-50.DOI:10.3969/j.issn.1006-3242.2005.01.011.
[8]汪柱,李树军,张立华,等.基于航路二叉树的航线自动生成方法[J].武汉大学学报(信息科学版),2010,35(4):407-410.DOI:10.13203/j.whugis2010.04.015.
[9]王莹,刘维亭.基于改进蚁群算法的舰船航路规划研究[J].现代电子技术,2010,33(21):186-188,196.DOI:10.16652/j.issn.1004-373x.2010.21.014.
[10]邹春明,赵俊超,杨柯,等.基于惩罚-PSO的群桥水域多约束航路规划[J].中国航海,2016,39(2):67-70.DOI:10.3969/j.issn.1000-4653.2016.02.016.
[11]刘俊丽,韩旭.遗传算法技术浅论[J].电脑学习,2009(5):142-143.DOI:10.3969/j.issn.2095-2163.2009.05.070.
[12]徐建国.岛礁区航行方法与应急措施[J].中国水运,1997(8):29-30.DOI:10.13646/j.cnki.42-1395/u.1997.08.015.
[13]吕呼平.浅谈大型船舶在舟山岛礁区航行的方法[C]//中国航海学会优秀论文文摘及学术会议论文目次汇编(1990-1991).上海,1992:2.
[14]张云鹏,张吉平.大型船舶沿岸航行富余水深的研究[J].大连海事大学学报,2014,40(3):33-36.DOI:10.16411/j.cnki.issn1006-7736.2014.03.017.
[15]栾法敏.沿岸通航密集区航行风险识别、评估和控制[J].中国航海,2014,37(3):80-84.DOI:10.3969/j.issn.1000-4653.2014.03.019.
[16]张锡海.曹妃甸港及其附近水域航路优化的研究[D].大连:大连海事大学,2007.DOI:10.7666/d.y1037209.
[17]马全党.典型水域船舶航路动态规划模型及其应用研究[D].武汉:武汉理工大学,2012.DOI:10.7666/d.y2099337.