Abstract

Scheduling of hygiene tasks in a food production environment is a complex challenge which is typically performed manually. Many factors must be considered during scheduling; this includes what training a hygiene operative (i.e. cleaning staff member) has undergone, the availability of hygiene operatives (holiday commitments, sick leave etc.) and the production constraints (how long does the oven take to cool, when does production begin again etc.). This paper seeks to apply multiagent task allocation (MATA) to automate and optimise the process of allocating tasks to hygiene operatives. The intention is that this optimization module will form one part of a proposed larger system. that we propose to develop. A simulation has been created to function as a digital twin of a factory environment, allowing us to evaluate experimentally a variety of task allocation methodologies. Trialled methods include Round Robin (RR), Sequential Single Item (SSI) auctions, Lowest Bid and Least Contested Bid.