A main purpose of a multi-objective evolutionary algorithm is to find a good relationship between convergence and diversity of the population. Convergence guides the algorithm to search the optimal solution and diversity tries to avoid a premature stagnation of the search. In multi-objective evolutionary algorithms, diversity has been promoted using different techniques. In this paper, several ...

Estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. This study aimed to use the particle swarm optimization (PSO) algorithm for automatic calibration of the HEC-HMS hydrologic model, which includes a library of different event-based models for simulating the rainfall-runoff pr...

aphasia diagnosis is a challenging medical diagnostic task due to the linguistic uncertainty and vagueness, large number of measurements with imprecision, inconsistencies in the definition of aphasic syndromes, natural diversity and subjectivity in test objects as well as in options of experts who diagnose the disease. in this paper we present a new self-organized multi agent system that diagno...

This paper is comprised of the modeling and optimization of a multi objective linear programming problem in fuzzy environment in which some goals are fractional and some are linear. Here, we present a new approach for its solution by using α-cut of fuzzy numbers. In this proposed method, we first define membership function for goals by introducing non-deviational variables for each of objective...

In practice, there are many problems which decision parameters are fuzzy numbers, and some kind of this problems are formulated as either possibilitic programming or multi-objective programming methods. In this paper, we consider a multi-objective programming problem with fuzzy data in constraints and introduce a new approach for solving these problems base on a combination of the multi-objecti...