A collaborative process planning and scheduling system
Advances in Engineering Software - Special issue: computer-aided process planning
Efficient scheduling of arbitrary task graphs to multiprocessors using a parallel genetic algorithm
Journal of Parallel and Distributed Computing - Special issue on parallel evolutionary computing
Hybrid negotiation for resource coordination in multiagent systems
Web Intelligence and Agent Systems
Multi-agent scheduling on a single machine to minimize total weighted number of tardy jobs
Theoretical Computer Science
Web Intelligence and Agent Systems
Collaborative Resource Constraint Scheduling with a Fractional Shared Resource
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Sequential multi-agent exploration for a common goal
Web Intelligence and Agent Systems
Hi-index | 0.00 |
We consider a collaborative scheduling problem motivated by mining in remote off-grid areas. In our model, jobs are preassigned to processors who have their own machine for executing them. Because each job needs a certain amount of a resource shared between the processors, a coordination mechanism between the processors is needed. We present a framework which collaboratively computes a schedule while exchanging only limited information between the processors and a central resource manager. Our computational experiments show that our negotiated approach outperforms a one-shot solution approach by a wide margin and produces fairer solutions than a centralised genetic algorithm that can make use of the private information of each processor. Depending on the number of processors, the solution quality found by the mechanism presented in this paper is competitive with or even better than that of the centralised genetic algorithm.