Heuristics on the Data-Collecting Robot Problem with Immediate Rewards

We propose the Data-collecting Robot Problem, where robots collect data as they visit nodes in a graph, and algorithms to solve it. There are two variations of the problem: the delayed-reward problem, in which robots must travel back to the base station to deliver the data collected and to receive rewards; and the immediate-reward problem, in which the reward is immediately given to the robots as they visit each node. The delayed-reward problem is discussed in one of the authors' work. This paper focuses on the immediate-reward problem. The solution structure has a clustering step and a tour-building step. We propose Progressive Gain-aware Clustering that finds good quality solutions with efficient time complexity. Among the six proposed tour-building heuristics, Greedy Insertion and Total-Loss algorithms perform best when data rewards are different.