Abstract
This paper deals with the minimization of the operational costs of business systems using the Artificial Immune System (AIS). The objective function consists of service costs and waiting costs. Service cost is the cost of hiring service-providing professionals, while waiting cost is the estimate of the loss to business as some customers, not willing to wait for service, decide to go to the competing organizations. Since business systems are inherently concurrent with multiple asynchronous activities, we have used Generalized Stochastic Petri Net as the modelling tool. The Petri net-modeled system is simulated by means of a discrete event simulator and optimized by means of the Artificial Immune System. Compared to the other meta-heuristic optimization algorithms like the Genetic Algorithm, the AIS is found to be simpler in implementation and better in performance.