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Evolutionary Multiobjective Optimization

by Ajith Abraham, Lakhmi Jain , 2005
"... ..."
Abstract - Cited by 21 (2 self) - Add to MetaCart
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Evolutionary Multiobjective Optimization for Green Clouds

by Dung H. Phan, Junichi Suzuki, William Donnelly, Raymond Carroll, Dmitri Botvich
"... As Internet data centers (IDCs) have been increasing in scale and complexity, they are currently a significant source of energy consumption and CO2 emission. This paper proposes and evaluates a new framework to operate a federation of IDCs in a “green ” way. The proposed framework, called Green Mons ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
Monster, dynamically moves services (i.e., workload) across IDCs for increasing renewable energy consumption while maintaining their performance. It makes decisions of service migration and placement with an evolutionary multiobjective optimization algorithm (EMOA) that evolves a set of solution

Evolutionary Multiobjective Optimization Approach For Evolving . . .

by Ajith Abraham, Crina Grosan, Sang Yong Han, Alexander Gelbukh - IN: A. GELBUKH (ED.), PROCEEDINGS OF THE FOURTH MEXICAN INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, MEXICO, LECTURE NOTES IN COMPUTER SCIENCE , 2005
"... The use of intelligent systems for stock market predictions has been widely established. This paper introduces a genetic programming technique (called Multi-Expression programming) for the prediction of two stock indices. The performance is then compared with an artificial neural network trained usi ..."
Abstract - Cited by 6 (2 self) - Add to MetaCart
obtained by these five techniques are combined using an ensemble and two well known Evolutionary Multiobjective Optimization (EMO) algorithms namely Nondominated Sorting Genetic Algorithm II (NSGA II) and Pareto Archive Evolution Strategy (PAES)algorithms in order to obtain an optimal ensemble combination

A Short Tutorial on Evolutionary Multiobjective Optimization

by Carlos A. Coello Coello , 2001
"... This tutorial will review some of the basic concepts related to evolutionary multiobjective optimization (i.e., the use of evolutionary algorithms to handle more than one objective function at a time). The most commonly used evolutionary multiobjective optimization techniques will be described and c ..."
Abstract - Cited by 44 (0 self) - Add to MetaCart
This tutorial will review some of the basic concepts related to evolutionary multiobjective optimization (i.e., the use of evolutionary algorithms to handle more than one objective function at a time). The most commonly used evolutionary multiobjective optimization techniques will be described

A Tutorial on Evolutionary Multiobjective Optimization

by Eckart Zitzler, Marco Laumanns, Stefan Bleuler - In Metaheuristics for Multiobjective Optimisation , 2003
"... Mu l ip often conflicting objectives arise naturalj in most real worl optimization scenarios. As evol tionaryalAxjO hms possess several characteristics that are desirabl e for this type of probl em, this clOv of search strategies has been used for mul tiobjective optimization for more than a decade. ..."
Abstract - Cited by 78 (0 self) - Add to MetaCart
Mu l ip often conflicting objectives arise naturalj in most real worl optimization scenarios. As evol tionaryalAxjO hms possess several characteristics that are desirabl e for this type of probl em, this clOv of search strategies has been used for mul tiobjective optimization for more than a decade

Current and Future Research Trends in Evolutionary Multiobjective Optimization

by Carlos A. Coello Coello, Gregorio Toscano Pulido, Efrén Mezura Montes , 2005
"... In this chapter we present a brief analysis of the current research performed on evolutionary multiobjective optimization. After analyzing first and second generation multiobjective evolutionary algorithms, we address two important issues: the role of elitism in evolutionary multiobjective optimiz ..."
Abstract - Cited by 5 (0 self) - Add to MetaCart
In this chapter we present a brief analysis of the current research performed on evolutionary multiobjective optimization. After analyzing first and second generation multiobjective evolutionary algorithms, we address two important issues: the role of elitism in evolutionary multiobjective

Fuzzy Optimality and Evolutionary Multiobjective Optimization

by M. Farina, P. Amato - Kalyanmoy Deb and Lothar Thiele (editors), Evolutionary Multi-Criterion Optimization. Second International Conference, EMO 2003 , 2003
"... Abstract. Pareto optimality is someway ineffective for optimization problems with several (more than three) objectives. In fact the Pareto optimal set tends to become a wide portion of the whole design domain search space with the increasing of the numbers of objectives. Consequently, little or no h ..."
Abstract - Cited by 8 (0 self) - Add to MetaCart
Abstract. Pareto optimality is someway ineffective for optimization problems with several (more than three) objectives. In fact the Pareto optimal set tends to become a wide portion of the whole design domain search space with the increasing of the numbers of objectives. Consequently, little

An Updated Survey of Evolutionary Multiobjective Optimization Techniques :

by State Of The, Carlos A. Coello Coello - Proceedings of the Congress on Evolutionary Computation , 1999
"... This paper reviews some of the most popular evolutionary multiobjective optimization techniques currently reported in the literature, indicating some of their main applications, their advantages, disadvantages, and degree of aplicability. Finally, some of the most promising areas of future research ..."
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This paper reviews some of the most popular evolutionary multiobjective optimization techniques currently reported in the literature, indicating some of their main applications, their advantages, disadvantages, and degree of aplicability. Finally, some of the most promising areas of future research

Evolutionary Multiobjective Optimization Using a Cultural Algorithm

by Carlos A. Coello Coello, Ricardo Landa Becerra - IEEE SWARM INTELLIGENCE SYMPOS., IEEE SERVICE CENTER, PISCATAWAY, NJ , 2003
"... In this paper, we present the first proposal to use a cultural algorithm to solve multiobjective optimization problems. Our proposal uses evolutionary programming, Pareto ranking and elitism (i.e., an external population). The approach proposed is validated using several examples taken from the spec ..."
Abstract - Cited by 21 (1 self) - Add to MetaCart
In this paper, we present the first proposal to use a cultural algorithm to solve multiobjective optimization problems. Our proposal uses evolutionary programming, Pareto ranking and elitism (i.e., an external population). The approach proposed is validated using several examples taken from

Handling Preferences in Evolutionary Multiobjective Optimization: A Survey

by Carlos A. Coello Coello - In 2000 Congress on Evolutionary Computation , 2000
"... Despite the relatively high volume of research conducted on evolutionary multiobjective optimization in the last few years, little attention has been paid to the decision making process that is required to select a final solution to the multiobjective optimization problem at hand. This paper reviews ..."
Abstract - Cited by 50 (3 self) - Add to MetaCart
Despite the relatively high volume of research conducted on evolutionary multiobjective optimization in the last few years, little attention has been paid to the decision making process that is required to select a final solution to the multiobjective optimization problem at hand. This paper
Results 1 - 10 of 12,478