Case Retrieval Strategy Based on GAs and Group Decision-Making Method
Wei Jiang, Aijun Yan, Pu Wang · 2010
Case retrieval is the focal stage in a Case-Based Reasoning (CBR) system. In this paper, a new case retrieval method called CRGCU is proposed in a systematical way, which is based on Genetic Algorithms (GAs) and Group Decision-Making method. First, feature attribute weights of cases are optimized by using GAs. Second, instead of utilizing only one set of feature attribute weights, we calculate similarity based on multiple sets of optimized weights. The result of case retrieval can be obtained at last by adopting Group Cardinal Utility function. The experiments on both static and dynamic data sets illustrate that our method is effective and suitable for CBR system.