A Heuristic Approach to the Problem of Min-Time Coverage in Constricted Environments

The problem of min-time coverage in constricted environments concerns the employment of networked robotic fleets for the support of routine inspection and service operations taking place in well-structured but constricted environments. In a series of previous works, we have provided a detailed definition of this problem, a mixed integer programming (MIP) formulation for it, a formal analysis of its worst case computational complexity, and additional structural results for its optimal solutions that also enable the solution of the problem through a partial relaxation of the original MIP formulation. The current work employs those past developments toward the development of a heuristic algorithm able to address larger problem instances that are not amenable to the previous methods. An accompanying set of numerical experiments demonstrates and assesses the computational advantages of this new method. Furthermore, the presented developments can function as building blocks for additional heuristic approaches to the considered problem; this potential is highlighted in the concluding part of this article.