Evolutionary Multiobjective Optimization Approach for Evolving Ensemble of Intelligent Paradigms for Stock Market Modeling

2005 ◽  
pp. 673-681 ◽  
Author(s):  
Ajith Abraham ◽  
Crina Grosan ◽  
Sang Yong Han ◽  
Alexander Gelbukh
Keyword(s):  
Stock Market ◽  
Multiobjective Optimization ◽  
Optimization Approach ◽  
Evolutionary Multiobjective Optimization

Design of combinational logic circuits through an evolutionary multiobjective optimization approach

2002 ◽  
Vol 16 (1) ◽  
pp. 39-53 ◽  
Author(s):  
CARLOS A. COELLO COELLO ◽  
ARTURO HERNÁNDEZ AGUIRRE
Keyword(s):  
Multiobjective Optimization ◽  
Population Based ◽  
Logic Circuits ◽  
Computational Effort ◽  
Lower Number ◽  
Optimization Approach ◽  
Combinational Circuits ◽  
Evolutionary Multiobjective Optimization ◽  
Combinational Logic Circuits ◽  
Human Designer

In this paper, we propose a population-based evolutionary multiobjective optimization approach to design combinational circuits. Our results indicate that the proposed approach can significantly reduce the computational effort required by a genetic algorithm (GA) to design circuits at a gate level while generating equivalent or even better solutions (i.e., circuits with a lower number of gates) than a human designer or even other GAs. Several examples taken from the literature are used to evaluate the performance of the proposed approach.

scholarly journals Multipurpose Water Reservoir Management: An Evolutionary Multiobjective Optimization Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Luís A. Scola ◽  
Ricardo H. C. Takahashi ◽  
Sérgio A. A. G. Cerqueira
Keyword(s):  
Multiobjective Optimization ◽  
Flood Control ◽  
Electric Energy ◽  
Water Reservoir ◽  
Optimization Approach ◽  
Operation Planning ◽  
Nsga Ii ◽  
Evolutionary Multiobjective Optimization ◽  
Hydropower Plants ◽  
The Cost

The reservoirs that feed large hydropower plants should be managed in order to provide other uses for the water resources. Those uses include, for instance, flood control and avoidance, irrigation, navigability in the rivers, and other ones. This work presents an evolutionary multiobjective optimization approach for the study of multiple water usages in multiple interlinked reservoirs, including both power generation objectives and other objectives not related to energy generation. The classical evolutionary algorithm NSGA-II is employed as the basic multiobjective optimization machinery, being modified in order to cope with specific problem features. The case studies, which include the analysis of a problem which involves an objective of navigability on the river, are tailored in order to illustrate the usefulness of the data generated by the proposed methodology for decision-making on the problem of operation planning of multiple reservoirs with multiple usages. It is shown that it is even possible to use the generated data in order to determine the cost of any new usage of the water, in terms of the opportunity cost that can be measured on the revenues related to electric energy sales.

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