Task scheduling for transport and pick robots in logistics: a comparative study on constructive heuristics

Abstract

We study the Transport and Pick Robots Task Scheduling (TPS) problem, in which two teams of specialized robots, transport robots and pick robots, collaborate to execute multi-station order fulfillment tasks in logistic environments. The objective is to plan a collective time-extended task schedule with the minimization of makespan. However, for this recently formulated problem, it is still unclear how to obtain satisfying results efficiently. In this research, we design several constructive heuristics to solve this problem based on the introduced sequence models. Theoretically, we give time complexity analysis or feasibility guarantees of these heuristics; empirically, we evaluate the makespan performance criteria and computation time on designed dataset. Computational results demonstrate that coupled append heuristic works better for the most cases within reasonable computation time. Coupled heuristics work better than decoupled heuristics prominently on instances with relative few pick robot numbers and large work zones. The law of diminishing marginal utility is also observed concerning the overall system performance and different transport-pick robot numbers.