  This paper solves a path planning problem for a group of gliders. The gliders
are tasked with visiting a set of interest points. The gliders have limited
range but are able to increase their range by visiting special points called
thermals. The problem addressed in this paper is of path planning for the
gliders such that, the total number of interest points visited by the gliders
is maximized. This is referred to as the multi-agent problem. The problem is
solved by first decomposing it into several single-agent problems. In a
single-agent problem a set of interest points are allocated to a single glider.
This problem is solved by planning a path which maximizes the number of visited
interest points from the allocated set. This is achieved through a uniform cost
graph search, as shown in our earlier work. The multi-agent problem now
consists of determining the best allocation (of interest points) for each
glider. Two ways are presented of solving this problem, a brute force search
approach as shown in earlier work and a Branch\&Bound type graph search. The
Branch&Bound approach is the main contribution of the paper. This approach is
proven to be optimal and shown to be faster than the brute force search using
simulations.
