summary:This paper shows how the simulated annealing (SA) algorithm provides a simple tool for solving fuzzy optimization problems. Often, the issue is not so much how to fuzzify or remove the conceptual imprecision, but which tools enable simple solutions for these intrinsically uncertain problems. A well-known linear programming example is used to discuss the suitability of the SA algorithm for solving fuzzy optimization problems
Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together w...
In modelling and optimizing real world systems and processes, one usually ends up with a linear or n...
AbstractA general approach to solving a wide class of optimization problems with fuzzy coefficients ...
summary:This paper shows how the simulated annealing (SA) algorithm provides a simple tool for solvi...
Simulated Annealing (SA) is a reasonable algorithm for solving optimization problems, through the se...
AbstractIn this paper, the hybridization of PS (Pattern Search) method and SA (Simulated Annealing) ...
Stochastic global optimization is a very important subject, that has applications in virtually all a...
Abstract. Fuzzy Linear Programming models and methods has been one of the most and well studied topi...
In a recent paper, Jiménez et al. (2007) propose a 'general' and 'interactive' method for solving li...
This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to mo...
This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to m...
This book describes recent advances on fuzzy logic augmentation of nature-inspired optimization meta...
The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming....
In this paper, we concentrate on three kinds of fuzzy linear programming problems: linear programmin...
This thesis reports the work of using simulated annealing to design more efficient fuzzy logic syste...
Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together w...
In modelling and optimizing real world systems and processes, one usually ends up with a linear or n...
AbstractA general approach to solving a wide class of optimization problems with fuzzy coefficients ...
summary:This paper shows how the simulated annealing (SA) algorithm provides a simple tool for solvi...
Simulated Annealing (SA) is a reasonable algorithm for solving optimization problems, through the se...
AbstractIn this paper, the hybridization of PS (Pattern Search) method and SA (Simulated Annealing) ...
Stochastic global optimization is a very important subject, that has applications in virtually all a...
Abstract. Fuzzy Linear Programming models and methods has been one of the most and well studied topi...
In a recent paper, Jiménez et al. (2007) propose a 'general' and 'interactive' method for solving li...
This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to mo...
This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to m...
This book describes recent advances on fuzzy logic augmentation of nature-inspired optimization meta...
The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming....
In this paper, we concentrate on three kinds of fuzzy linear programming problems: linear programmin...
This thesis reports the work of using simulated annealing to design more efficient fuzzy logic syste...
Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together w...
In modelling and optimizing real world systems and processes, one usually ends up with a linear or n...
AbstractA general approach to solving a wide class of optimization problems with fuzzy coefficients ...