simultaneous optimization of multiple criteria for efficient agent service brokering
Efficient, flexible and dynamic allocation of combination of services to satisfy advanced service requirements in multi- agent systems is a crucial problem. Optimal service allocation based on a single criterion is NP- Complete. However, service requirements in general have multiple criteria that may be conflicting and noncommensurable. This paper presents a genetic algorithm for optimal anytime service allocation based on multiple criteria. The solution found by the genetic algorithm is optimal in terms of the information (criterion weighting and minimize/ maximize criterion) provided by the client. We present our algorithm and show how the performance of the algorithm varies as the number of criteria varies. The results show the performance of the algorithm is sublinear as the number of criteria increases. The algorithm has the ability to deal with any number of criteria. By addressing this problem, we expand the range of problems being addressed to any that require simultaneous optimization of multiple criteria.
brokers genetic algorithms matchmakers artificial market systems routers electronic commerce