A linear-programming model for use in analysis and planning of multiobjective water resources systems is described in this paper. A typical system consists of reservoirs, hydropower stations, irrigated land, artificial and navigation channels, etc., over a reach of a river or a river basin. The linear programming approach is studied and compared with other approaches: mixed integer-linear dynam...

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 the paper we present a new iterative method for solving multiobjective linear programming problems with an arbitrary number of decision makers. The method is based on the principles of game theory. Each step of the method yields a unique solution which respects the aspirations of decision makers within the frame of given possibilities. Each decision maker is assigned an objective indicator w...

A robust optimization approach is proposed for generating nondominated robust solutions for multiobjective linear programming problems with imprecise coefficients in the objective functions and constraints. Robust optimization is used in dealing with impreciseness while an interactive procedure is used in eliciting preference information from the decision maker and in making tradeoffs among the...

ABSTRACT: Feasible solutions of Bilevel programming (BLP) problem have to satisfy the optimality conditions of a lower level optimization problem which is defined as part of its constraints. Multiobjective BLP (MOBLP) problems are the special case of BLP problems with multiple objectives at the upper level which require every feasible solution to satisfy the Pareto optimality conditions of a lo...

In this paper, we study measurement of sensitivity for changes of violations in the aspiration level for the fuzzy multiobjective linear fractional programming problem. c © 2001 Elsevier Science B.V. All rights reserved.

This paper presents a neural network for solving non-linear minimax multiobjective fractional programming problem subject to nonlinear inequality constraints. Neural model is designed for optimization with constraints condition. Methodology is based on the lagrange multiplier with saddle point optimization.

This paper presents a method to solve a linear or nonlinear Fuzzy Multiobjective Programming problem. We propose Genetic Search based approaches to the case in which fuzzy constraints are assumed.

We study a general multiobjective optimization problem with variational inequality, equality, inequality and abstract constraints. Fritz John type necessary optimality conditions involving Mordukhovich coderivatives are derived. They lead to Kuhn-Tucker type necessary optimality conditions under additional constraint qualifications including the calmness condition, the error bound constraint qu...