Title: Using genetic algorithm for the evaluation of process variants

Authors: Tim Neumann; Tobias Teich; Joerg Militzer; Daniel Kretz

Addresses: University of Applied Sciences Zwickau, Dr.-Friedrichs-Ring 2a, 08058 Zwickau, Germany ' University of Applied Sciences Zwickau, Dr.-Friedrichs-Ring 2a, 08058 Zwickau, Germany ' University of Applied Sciences Zwickau, Dr.-Friedrichs-Ring 2a, 08058 Zwickau, Germany ' University of Applied Sciences Zwickau, Dr.-Friedrichs-Ring 2a, 08058 Zwickau, Germany

Abstract: Individual customer demands, price pressure and the probability to deliver at the required date and time are important factors for small and medium sized enterprises (SME). These companies, often in the branch of single-part or small-series production, want to be the supplier for larger companies. Decision makers in large companies have to investigate potential suppliers due to these mostly interrelated criteria. Considering different variants of manufacturing a product and the premature investigation of resources and there capacities make it possible to increase known factors during the proposal preparation. Therefore, this paper is introducing a conceptual framework for the evaluation of different process variants to manufacture a product. In this framework, we are using genetic algorithms to optimise and evaluate process variants including the necessary resources and their capacitive use in an evaluated period.

Keywords: genetic algorithms; process variants; ISO 10303; process planning; feature-based design; scheduling; small and medium-sized enterprises; SMEs; manufacturing industry.

DOI: 10.1504/IJSOI.2016.080086

International Journal of Services Operations and Informatics, 2016 Vol.8 No.2, pp.104 - 121

Accepted: 28 Sep 2015
Published online: 01 Nov 2016 *

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