A Multi-objective Optimization Method for Product Feature Fatigue Problem

Product feature fatigue is a common problem in practice. At the moment of purchasing, customers prefer to choose products with more features. After having used these high-feature products, customers become frustrated or dissatisfied with the usability problems caused by too many features. To deal with product feature fatigue problem, this paper introduces a novel model in which capability and complexity are regarded as two conflicting objects, and NSGA-II is adopted to search for a set of Pareto solutions for this multi-objective optimization problem. Then, this paper establishes piecewise linear membership functions based on decision maker's preferences, and a priority list of non-dominated solutions can be provided according to the membership function values. The list can make it easier for decision makers to make final selection. A smart phone case study shows that the proposed method is a powerful decision-aid tool for product designers when dealing with feature fatigue problem.

[1]  Christer Carlsson,et al.  Fuzzy multiple criteria decision making: Recent developments , 1996, Fuzzy Sets Syst..

[2]  I. Simonson,et al.  The Effect of New Product Features on Brand Choice , 1996 .

[3]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[4]  Mitsuo Gen,et al.  Genetic algorithms and engineering optimization , 1999 .

[5]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[6]  David A. Carr,et al.  Usability of mobile phones , 2003 .

[7]  Roland T. Rust,et al.  Feature Fatigue: When Product Capabilities Become Too Much of a Good Thing , 2005 .

[8]  Mitsuo Gen,et al.  Genetic Algorithms , 1999, Wiley Encyclopedia of Computer Science and Engineering.

[9]  Liyan Tao,et al.  Machining scheme selection of digital manufacturing based on genetic algorithm and AHP , 2009, J. Intell. Manuf..

[10]  Brett R. Gordon,et al.  Competitive Strategy for Open Source Software , 2011, Mark. Sci..

[11]  Xiaohui Xu,et al.  An analysis of consumer training for feature rich products , 2011, Decis. Support Syst..

[12]  Aruna Lakshmanan,et al.  The Aha! Experience: Insight and Discontinuous Learning in Product Usage , 2011 .

[13]  Ming Li,et al.  Feature fatigue analysis in product development using Bayesian networks , 2011, Expert Syst. Appl..

[14]  M Wu,et al.  A continuous fuzzy Kano’s model for customer requirements analysis in product development , 2012 .

[15]  Ming Li,et al.  A multi-objective genetic algorithm approach for solving feature addition problem in feature fatigue analysis , 2013, J. Intell. Manuf..