Solving the machine-loading problem in a flexible manufacturing system using a combinatorial auction-based approach

The next generation manufacturing system is conceived to be intelligent enough to take decisions and automatically adjust itself to situations such as variations in production demand and machine breakdowns. The manufacturing control system must have the intelligence to ensure real time operational control by interacting with different manufacturing subsystems. One of the prominent methodologies to deal with the problem of distributed manufacturing systems is the auction-based heuristic control strategy in which various entities bid themselves, accept bids and make selection amongst bids. The present paper addresses the flexible manufacturing system machine-loading problem where job selection and operation allocation on machines are to be performed such that there is a minimization of system unbalance and a maximization of throughput. The methodology of winner determination using the combinatorial auction process is employed to solve the flexible manufacturing system machine-loading problem. In the combinatorial auction, allowing bidding on a combination of assets offers a way to enhance the efficiency of allocating the assets. The performance of the proposed approach is tested on 10 sample problems and the results thus obtained are compared with the existing models in the literature.