Obsolescence risk optimization using fuzzy logic and genetic algorithm

Component obsolescence is a fact causing high values of losses and management costs. It always happens when some components of a complex system have the life time less than the expected life time for the whole system. Artificial Intelligence fields could help managers with component obsolescence problem. There have been lots of researches focusing on key factors of component obsolescence risk but there is a gap in the way of choosing low risk components from the view of business intelligence. In this paper an innovative framework is presented using genetic algorithm and fuzzy logic that chooses the best components among the available alternatives. The result would be the best mixture of components with lowest component obsolescence risk. Obsolescence impact, obsolescence happening probability and the obsolescence time of each available component are considered as key factors of obsolescence risk management.