Modified Weighted Sum Method for Decisions with Altered Sources of Information

Adaptive Weighted Sum Method for Multiobjective Optimization

This paper presents an adaptive weighted sum method for multiobjective optimization problems. The authors developed the bi-objective adaptive weighted sum method, which determines uniformly-spaced Pareto optimal solutions, finds solutions on non-convex regions, and neglects non-Pareto optimal solutions. However, the method could solve only problems with two objective functions. In this work, th...

Various Information Sources for HMM with Weighted Multiple Codebooks

When semicontinuous HMM are used for acoustic modeling in speech recognition usually all states share a single codebook. In our investigations we split the feature set into independent subsets and use separate codebooks for each part. This provides a higher modeling flexibility while keeping the parameter space compact. Further experiments integrate new information sources by using additional c...

Limitations of Weighted Sum Measures for Information Quality

In an age dominated by information, information quality (IQ) is one of the most important factors to consider for obtaining competitive advantages. The general approach to the study of IQ has relied heavily on management approaches, IQ frameworks and dimensions. There are many IQ measures proposed, however dimensions in most frameworks are analyzed and assessed independently. Approaches to aggr...

Adaptive Weighted Sum Method for Bi-objective Optimization

This paper presents a new method that effectively determines a Pareto front for biobjective optimization with potential application to multiple objectives. A traditional method for multiobjective optimization is the weighted sum method, which seeks Pareto optimal solutions one by one by systematically changing the weights among the objective functions. Previous research has shown that this meth...

A Method for Defuzzication by Weighted Distance