Low-thrust global optimization (Nuclear electric propulsion)
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.. figure:: ../images/gallery1.png
   :alt: "Eart-Mars low-thrust transfer"
   :align: left

This plot is produced by the following code:

.. code-block:: python

   from PyKEP import *
   kep_examples.run_example1(nseg=40)

after the monotonic basin hopping algorithm concludes its computations. Different images are actually produced each time as
the algorithm is non-deterministic.

This example demonstrates the use of the Sims-Flanagan module of PyKEP to perform global optimization of a single leg interplanetary
trajectory over large launch windows. In particular, it defines a
transfer between the Earth and Mars as an NLP global optimization problem (using the open source `PyGMO project <http://pagmo.sourceforge.net/pygmo/index.html>`_)
and it then attempts to find one solution using the Monotonic Basin Hopping meta-algorithm connected to an SQP local optimization technique (from SciPy). In case
the user has a license for SNOPT, the use of this typically result in a performance gain

The code for this example can be studied `here 
<http://sourceforge.net/p/keptoolbox/code/ci/ef0454a6a69403a1786a4e7920c3fe036a916ad2/tree/PyKEP/examples/_ex1.py>`_

A reference where the methodology is studied more in depth is:

C H Yam, D D Lorenzo, D Izzo: `Low-thrust trajectory design as a constrained global optimization problem <http://pig.sagepub.com/content/early/2011/08/09/0954410011401686.abstract>`_  doi: 10.1177/0954410011401686
Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering August 10, 2011