System\u27s reability optimization problems are modeled using fuzzy nonlinier mix-integer goal programming problems, involving imprecise nonlinier mix-integer information. Furthermore, fuzzy nonlinier mix-integer goal programming is transformed into nonlinier mix-integer programming problem and the problem i solved using genetic algorithms by means of Matlab 5.3 software. The results or genetic algorithms with operator arithmetic crossover are the large of initial population number does not give the better fitness and the more generation numbers will result more high fitness
Most real-life optimisation problems involve multiple objective functions.Finding a solution that sa...
Fuzzy assignment problems is a special case linear programming model problems that allocate resourc...
AbstractThis article presents an effective genetic algorithm (GA) based fuzzy goal programming (FGP)...
This paper introduces a priority based fuzzy goal programming (FGP) method for modelling and solving...
Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together w...
. ABSTRACT This research is aimed at finding solutions in multiobjective integer programming prob...
AbstractFuzzy optimization is a well-known optimization problem in artificial intelligence, system c...
This paper proposes a generalized domain optimization method for fuzzy goal programming with differe...
Genetic algorithms are adaptive methods that use principles inspired by natural population genetics ...
The performance of a genetic algorithm is dependent on the genetic operators, in general, and on the...
AbstractFuzzy optimization is a well-known optimization problem in artificial intelligence, manufact...
There is uncertainty that the crisp function in classic regression analysis presents the relationshi...
Evolutionary algorithms, and genetic algorithms in particular, are generally time consuming when loo...
We focus on multiobjective nonlinear integer programming problems with block-angular structures whic...
Creating or preparing Multi-objective formulations are a realistic models for many complex engineeri...
Most real-life optimisation problems involve multiple objective functions.Finding a solution that sa...
Fuzzy assignment problems is a special case linear programming model problems that allocate resourc...
AbstractThis article presents an effective genetic algorithm (GA) based fuzzy goal programming (FGP)...
This paper introduces a priority based fuzzy goal programming (FGP) method for modelling and solving...
Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together w...
. ABSTRACT This research is aimed at finding solutions in multiobjective integer programming prob...
AbstractFuzzy optimization is a well-known optimization problem in artificial intelligence, system c...
This paper proposes a generalized domain optimization method for fuzzy goal programming with differe...
Genetic algorithms are adaptive methods that use principles inspired by natural population genetics ...
The performance of a genetic algorithm is dependent on the genetic operators, in general, and on the...
AbstractFuzzy optimization is a well-known optimization problem in artificial intelligence, manufact...
There is uncertainty that the crisp function in classic regression analysis presents the relationshi...
Evolutionary algorithms, and genetic algorithms in particular, are generally time consuming when loo...
We focus on multiobjective nonlinear integer programming problems with block-angular structures whic...
Creating or preparing Multi-objective formulations are a realistic models for many complex engineeri...
Most real-life optimisation problems involve multiple objective functions.Finding a solution that sa...
Fuzzy assignment problems is a special case linear programming model problems that allocate resourc...
AbstractThis article presents an effective genetic algorithm (GA) based fuzzy goal programming (FGP)...