Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Integration of environmental considerations in quality function deployment by using fuzzy logic
Expert Systems with Applications: An International Journal
Customer pattern search for after-sales service in manufacturing
Expert Systems with Applications: An International Journal
Quantitative modeling of customer perception from service data using evolutionary optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
| Hi-index | 12.05 |
This paper presents an approach to assess quality and reliability related customer satisfaction from field failure data at each individual customer level. The quality satisfaction has been modeled based on number of failures and severity of failures, while, reliability satisfaction has been modeled based on number of visits to dealer and time span between visits. The satisfaction modeled at an individual vehicle (customer) level is further aggregated to a vehicle model level to determine overall satisfaction of customers with that specific vehicle model. A fuzzy logic approach is used to construct the satisfaction model. A grid search technique is used to tune the model parameters such that the output of the model for specific vehicle models matches with survey based ratings assigned to the vehicle models.