Title :
Evaluation of a Genetic Algorithm based service productivity optimization
Author :
Tackenberg, S. ; Rieder, S. ; Duckwitz, S. ; Schlick, C.M.
Author_Institution :
Inst. of Ind. Eng. & Ergonomics, RWTH Aachen Univ., Aachen, Germany
Abstract :
The development of efficient service projects is a critical success factor for companies. Often this goal can only be realized by developing project plans. The process of planning a service and optimizing the underlying project plan still lacks adequate knowledge and support. Existing approaches are not suitable for an optimization of services with regard to productivity prior to their implementation. To achieve improved service productivity, novel operations of a Genetic Algorithm (GA) for the prospective optimization of service projects are presented and benchmarked with plans developed by humans. As a result, managers will be able to develop service organizations related to optimal service productivity and thus avoid cost intensive false decisions.
Keywords :
genetic algorithms; organisational aspects; production planning; productivity; service industries; critical success factor; genetic algorithm; project plan; service planning; service productivity optimization; Benchmark testing; Biological cells; Lead; genetic algorithm; optimization; plan effectiveness; plan efficiency; service productivity;
Conference_Titel :
Industrial Engineering and Engineering Management (IE&EM), 2010 IEEE 17Th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6483-8
DOI :
10.1109/ICIEEM.2010.5646032