In designing non-linear classifiers, there are important trade-offs to be made between predictive accuracy and model comprehensibility or complexity. We introduce the use of Genetic Programming to generate logistic polynomial models, a relatively comprehensible non-linear parametric model; describe an efficient twostage algorithm consisting of GP structure design and Quasi-Newton coefficient se...

In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stochastic linear programming problems, but also multiobjective fuzzy random linear programming problems through a probability maximization model. In a probability maximization model, it is necessary for the decision maker to specify permissible values of objective functions in advance, which have a great infl...

⎯In this paper we propose a methodology for the solution of multiobjective programming problem with fuzzy relational equations (FRE’s) as constraints. In the first part of the proposed methodology, we find the feasible solution set of FRE’s and give an algorithm to compute minimal solutions and maximal solutions of objective functions which can also be computed by constructed computer program a...