design space pruning heuristics and global optimization method for ...

OptimalTwo-Impulse J (kg/yr)
200
180
160
140
120
100
80
60
40
2 4 6 8 10 12 14
Time of Flight (years)
OptimalTwo-Impulse J (kg/yr)
200
180
160
140
120
100
80
60
40
2 4 6 8 10 12 14
Time of Flight (years)
Figure 52: Optimal impulsive solutions, with and without the time of flight restriction, for the
modified GTOC2 problem.
Table 22 lists the settings used for the genetic algorithm as applied to this
problem, and Table 23 lists the design variables, bounds, and discretization. The number
of bits for each design variable was chosen so that the discretization on all of the time
variables was approximately equal. For the bits chosen, the variables are discretized in
approximately seven day increments. Because of the greater number of low-thrust
optimizations required in this problem, the genetic algorithm is run only once for each
asteroid sequence. At the end of the branch-and-bound algorithm, the genetic algorithm
is then run three times on the most promising solutions, in an attempt to improve upon
their objective functions. Using these settings, on average, a single run of the genetic
algorithm requires 1746 function calls (end-to-end optimizations by MALTO) and 49
generations to converge. With the available computing resources, each genetic algorithm
run takes 70 minutes on average.
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