A Novel Multi-Agent System for Complex Scheduling Problems
This addresses scheduling challenges for domains requiring efficient computation, but it appears incremental as it builds on existing agent-based methods.
The paper tackles complex scheduling problems by proposing a multi-agent system with specialized agents and simulation-based optimization heuristics, demonstrating its validity on an NP-hard scheduling problem with advantages such as reduced layout complexity and improved control.
Complex scheduling problems require a large amount computation power and innovative solution methods. The objective of this paper is the conception and implementation of a multi-agent system that is applicable in various problem domains. Independent specialized agents handle small tasks, to reach a superordinate target. Effective coordination is therefore required to achieve productive cooperation. Role models and distributed artificial intelligence are employed to tackle the resulting challenges. We simulate a NP-hard scheduling problem to demonstrate the validity of our approach. In addition to the general agent based framework we propose new simulation-based optimization heuristics to given scheduling problems. Two of the described optimization algorithms are implemented using agents. This paper highlights the advantages of the agent-based approach, like the reduction in layout complexity, improved control of complicated systems, and extendability.