Auction-Based Job Scheduling for Smart Manufacturing.

The paper describes a real-time job scheduling method designed for production of goods with different characteristics on machines with different processing parameters. The objective is to maximize the global reward of the factory as a sum of the rewards for each machine job. Traditionally, the task assignment problems deal with the assignment of m-tasks to n-agents and are calculated by analytical methods or heuristics. The proposed method is based on online auctions that distributes the tasks to the machines using the software agents. The method is implemented using the ERTS (Erlang Real-Time System) that allows adopting the features of fault-tolerance and real-time processing. The paper starts with introduction and review of related state-of-the-art. The following chapter briefly describes the problem and the specific requirements. The following chapter describes the software architecture of the online auction system, the use-case and the motivation for developing this method. The proposed method auction-based task assignment and its implementation are described in the next chapters. At the end of the work, the results of the method are presented in comparison with the optimal solution and the performance characteristics are also described. In the conclusion, possible advances and future work are proposed.