- author = "Qirong Tang and Yinghao Li and Zhenqiang Deng and Di Chen and Ruiqin Guo and Hai Huang",
- title = "Optimal Shape Design of an Autonomous Underwater Vehicle Based on Gene Expression Programming",
- booktitle = "9th International Conference Advances in Swarm Intelligence, ICSI 2018, Part II",
- editor = "Ying Tan and Yuhui Shi and Qirong Tang",
- volume = "10942",
- series = "Lecture Notes in Computer Science",
- pages = "132--141",
- address = "Shanghai, China",
- month = jun # " 17-22",
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, gene expression programming, Autonomous underwater vehicle, Shape optimization, Multi-objective particle swarm optimization, PSO",
- isbn13 = "978-3-319-93817-2",
- bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/swarm/icsi2018-2.html#TangLDCGH18",
-
DOI = "
10.1007/978-3-319-93818-9_13",
- abstract = "A novel strategy combining gene expression programming and crowding distance based multi-objective particle swarm algorithm is presented in this paper to optimize an underwater robot’s shape. The gene expression programming method is used to establish the surrogate model of resistance and surrounded volume of the robot. After that, the resistance and surrounded volume are set as two optimized factors and Pareto optimal solutions are then obtained by using multi-objective particle swarm optimization. Finally, results are compared with the hydrodynamic calculations. Result shows the efficiency of the method proposed in the paper in the optimal shape design of an underwater robot.",
-
notes = "conf/swarm/TangLDCGH18
Laboratory of Robotics and Multibody System, School of Mechanical Engineering, Tongji University, Shanghai, 201804, People Republic of China",
