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Participatory evolution is a learning paradigm recently introduced in the realm of fuzzy system modeling and system optimization. The paradigm benefits from the concept of participatory learning, genetic algorithms and differential evolution. In this paper we address two distinct participatory evolutionary learning algorithms. The first combines participatory learning and the processing steps of differential...
Genetic Fuzzy Systems have been successfully used as a modeling approach for numerous applications. There is an increasing interest on how to construct fuzzy models for different types of complex systems such as highly nonlinear, large-scale, multiobjective, and high-dimensional systems. Current state of the art indicates the use of fast and scalable evolutionary algorithms in complex fuzzy modeling...
Modeling the term structure of government bond yields is of major interest to macroeconomists and financial market practitioners. It is crucial for bonds and derivatives pricing, risk management, revealing market expectations, and essential for monetary policy decisions. This paper proposes the use of differential evolution to estimate the term structure of government bond yields considering parsimonious...
This paper introduces a genetic fuzzy system to control short and long term memory of tabu search algorithms. The genetic fuzzy system involves learning of the knowledge base and a rule selection procedure. The aim is to trade-off exploration and exploitation behavior of the search, and to handle high dimensional optimization problems. The genetic fuzzy system approach introduces a high level of autonomy...
This paper presents a genetic algorithm coordinated by fuzzy rule models to solve the vehicle routing problem with time windows. The fuzzy rule-based coordinators play distinct roles during the genetic algorithm execution. The aim is to trade-off exploration and exploitation behavior for route and distance minimization. Experimental results using classic benchmark test instances suggest that the fuzzy...
In this paper a coevolutionary genetic approach is devised to support hierarchical, collaborative relations between individuals representing different parameters of Takagi-Sugeno fuzzy models. The coevolutionary approach assumes species to mean partial solutions of fuzzy modeling problems organized into four hierarchical levels. Individuals at each hierarchical level encode membership functions, individual...
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