A hierarchical multi-color spraying path planning with clustered traveling salesman problem

This paper presents a new method to solve the problem of multi-color spraying path planning. This method uses hierarchical optimization strategy to solve multi-color spraying path planning problem. The problem is broken down into two smaller subproblems: the upper-level clustered traveling salesman problem (CTSP) and the lower-level route case selection problem. To solve the problem of upper-level CTSP, we use genetic algorithm (GA) with multi-subpopulation initialization (MSI) approach. To solve the problem of lower-level route case selection, we use a greedy method (GM) and a tabu search (TS) algorithm. Color blocks of the same color must be continuously sprayed. The gun returns to its starting point after completing the task. The goal of multi-color spraying path planning is to find a minimum cost path for a gun to move between color blocks.