Figure 4. (a) The left graph shows a plot of a cost function for a problem with a well defined global minimum cost as well as several local minima. Cost is plotted on the vertical axis and position on the horizontal axis labels the particular stage of some iterative planning cycle. For example, the global minimum corresponds to having achieved the beams which deliver dose best matching the prescribed constraints. The very left hand position might represent the start of iteration when beams have not yet been properly formed. (b) The right graph conversely shows a cost function more typical of radiotherapy inverse planning problems. There is a wide plateau (basin) of beam arrangements all of which correspond to dose distributions that are much the same and best satisfy the planning constraints. There may be a small dip (global minimum) for the absolute best but continuing the iteration to find this might be futile when any position in the plateau would be acceptable.