Abstract

New paradigms for designing manufacturing systems, such as adaptive and service-oriented manufacturing systems or self-optimizing resources, introduce new degrees of freedom into manufacturing control. These paradigms lead to the research question how human decision makers can be enabled to exploit the high adaptability of the new manufacturing systems in accordance to the current requirements arising from quickly changing market requirements and demand for sustainable manufacturing. This contribution extends a scheduling model for self-optimizing and service-oriented manufacturing systems through the consideration of alternative resources and introduces a multi-objective scheduling concept based on evolutionary algorithms in combination with a new optimized type of crossover operator.

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