Multi-Robot Routing Problem with Min–Max Objective

In this paper, we study the “Multi-Robot Routing problem” with min–max objective (MRR-MM) in detail. It involves assignment of sequentially ordered tasks to robots such that maximum cost slowest robot is minimized. The problem description, different types formulations, and methods used across various research communities are discussed paper. We propose a new formulation by treating as permutation matrix. A comparative done between three methods: Stochastic simulated annealing, deterministic mean-field heuristic-based graph search method. Each method investigated detail several data sets (simulation real-world), results analysed compared respect scalability, computational complexity, optimality, its application real-world scenarios. paper shows heuristic produces very quickly good scalability. However, solution quality sub-optimal. On other hand, when optimal or near-optimal required considerable resources, annealing proves be more efficient. show choice algorithm depends on dataset size available budget. contribution three-fold: MRR-MM communities. This also lack inter-research terminology has led names for same problem. Secondly, formulating task allocation matrix opened up approaches solve Thirdly, applied our conducted detailed using simulation data.