Multi-criteria optimization of service productivity using evolutionary algorithm

The research presented is concerned with the planning component of service management and describes the use of a multiobjective evolutionary heuristic to optimize the productivity of service projects. Adequate planning assures the effective and efficient use of resources, customer satisfaction and the attainment of service objectives in an acceptable period of time. In order to achieve improved service productivity, the concepts for planning are reviewed and an optimization algorithm for a resource constrained service model is introduced. Thereby, our vision is a supporting system for planers using a multi-criteria optimization algorithm (SMSEMOA) to reduce the risk of service development. Therefore, our approach integrates the bounded rational decision making of actors and leads to a priori optimal adjustment of relevant factors like the interaction between customers and the service provider.