Abstract
The practical approach and multi-agent platform development for adaptive scheduling systems for real time resource management are considered. The approach is based on concept of demand and resource networks (DRN) where agents of demands and resources operate on virtual market and continuously trying to improve their individual values of satisfaction functions that reflects given multi-criteria objectives. To achieve the best possible results agents use the virtual money account that regulates their behavior and can increase by getting bonuses or decrease by penalties depending of their individual cost functions. The key rule of designed virtual market is that any agent that is searching for new better position in schedule must compensate losses for those conflicting agents who are able and agree to change their allocations to other resources after the initial agent request, with required amount of compensation determined in the process of re-allocations. This approach allows to balance many criteria for getting consensus between agents and adaptation of the schedules “on the fly” by events without any stop and restart of the system. The developed platform includes key classes of DRN agents and protocols of their negotiations and other components that help to develop the solution manage data and visualize results of scheduling. The platform provides rapid prototyping of multi-agent systems for real time resource management and helps to reduce man-efforts and time of development. The platform was applied for developing of multi-agent scheduling systems for managing resources in aircraft jet production, load balancing in computer grid networks and energy production in power-, gas- and heating networks.
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Skobelev, P., Budaev, D., Laruhin, V., Levin, E., Mayorov, I. (2014). Practical Approach and Multi-agent Platform for Designing Real Time Adaptive Scheduling Systems. In: Corchado, J.M., et al. Highlights of Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection. PAAMS 2014. Communications in Computer and Information Science, vol 430. Springer, Cham. https://doi.org/10.1007/978-3-319-07767-3_1
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DOI: https://doi.org/10.1007/978-3-319-07767-3_1
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