Figure 3

The greedy algorithm divides the optimization problem (6) into several smaller optimization problems that are easier to solve. The procedure involves a division of the beam path into subintervals. Localized optimization problems are solved on these intervals and optimal parameters are frozen in steps. After each such step, a new sub-problem is created by translating in time (ans space) and updating the initial condition. Here \(q=p+3\) and \(r=1\) (see Algorithm 1).