Path bundling, a class of path planning problem, consists of compounding multiple routes to minimize a global distance metric. Naturally, a tree-like structure is obtained as a result wherein roots play the role of coordinating the joint transport of information, goods, and people. In this paper we tackle the path bundling problem in bipartite networks by using gradient-free optimization and a convex representation. Then, by using 7,500 computational experiments in diverse scenarios with and without obstacles, implying 7.5 billion shortest path computations, show the feasibility and efficiency of the mesh adaptive search.