A new foraging-based algorithm for online scheduling

Abstract

While much work exists on scheduling, literature in the subfield of online scheduling remains sparse. As with many problems, online scheduling has parallels with natural phenomena. Specifically, online scheduling can be seen in the division of labour among colony insects, such as ants. Although multiple different biological models exist for division of labour, the only one to have been applied in online scheduling is the reinforced threshold model, for instance in the form of the ant task allocation (ATA) algorithm. However, it is neither known how it compares to other models, nor in which applications any of them excel. This paper studies the foraging for work (FFW) model as a possible alternative. To do so, an algorithmic description of the FFW model is introduced, and it is compared with the ATA algorithm on the truck painting problem. For this problem, tasks of various types are scheduled in a flowshop with multiple identical machines in an online fashion. FFW is shown to be very effective at minimising setup time, which is incurred when switching to tasks of different types. Furthermore, this allows FFW to outperform the threshold based approaches when the scheduling environment is placed under heavy load.