Multiobjective Design Exploration of a Many-objective Space Trajectory Problem for Low-Thrust Spacecraft Using MOEA with Large Populations

Author(s):  
Tomoaki Tatsukawa ◽  
Takeshi Watanabe ◽  
Akira Oyama ◽  
Kozo Fujii
2017 ◽  
Vol 54 (4) ◽  
pp. 796-807
Author(s):  
Takeshi Watanabe ◽  
Tomoaki Tatsukawa ◽  
Takayuki Yamamoto ◽  
Akira Oyama ◽  
Yasuhiro Kawakatsu

2018 ◽  
Vol 16 (2) ◽  
pp. 144-163 ◽  
Author(s):  
John Harding ◽  
Cecilie Brandt-Olsen

Combining graph-based parametric design with metaheuristic solvers has to date focused solely on performance-based criteria and solving clearly defined objectives. In this article, we outline a new method for combining a parametric modelling environment with an interactive Cluster-Orientated Genetic Algorithm. In addition to performance criteria, evolutionary design exploration can be guided through choice alone, with user motivation that cannot be easily defined. As well as numeric parameters forming a genotype, the evolution of whole parametric definitions is discussed through the use of genetic programming. Visualisation techniques that enable mixing small populations for interactive evolution with large populations for performance-based optimisation are discussed, with examples from both academia and industry showing a wide range of applications.


2014 ◽  
Vol 2014.11 (0) ◽  
pp. _1218-1_-_1218-5_
Author(s):  
Akira OYAMA ◽  
Tomoaki TATSUKAWA ◽  
Takeshi WATANABE

2013 ◽  
Vol 2013 (0) ◽  
pp. _0634-01_-_0634-05_
Author(s):  
Tomoaki Tatsukawa ◽  
Yuki Nagata ◽  
Makoto Yamamoto ◽  
Taku Nonomura ◽  
Akira Oyama ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document