Results 1 - 10 of 154

A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II

by Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, T Meyarivan , 2000
"... Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) -4 computational complexity (where is the number of objectives and is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing ..."
Abstract - Cited by 662 (15 self) - Add to MetaCart
sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algorithm (we called it the Non-dominated Sorting GA-II or NSGA-II) which alleviates all the above three difficulties. Specifically, a fast non-dominated sorting approach with computational

A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II

by Kalyanmoy Deb, Amrit Pratap, Sameer Agarwal, T. Meyarivan , 2000
"... Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) O(MN computational complexity (where M is the number of objectives and N is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing param ..."
Abstract - Cited by 1815 (60 self) - Add to MetaCart
parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algorithm (we called it the Non-dominated Sorting GA-II or NSGA-II) which alleviates all the above three difficulties. Specifically, a fast non-dominated sorting approach with O(MN ) computational complexity

Approximating the nondominated front using the Pareto Archived Evolution Strategy

by Joshua D. Knowles, David W. Corne - EVOLUTIONARY COMPUTATION , 2000
"... We introduce a simple evolution scheme for multiobjective optimization problems, called the Pareto Archived Evolution Strategy (PAES). We argue that PAES may represent the simplest possible nontrivial algorithm capable of generating diverse solutions in the Pareto optimal set. The algorithm, in its ..."
Abstract - Cited by 321 (19 self) - Add to MetaCart
of the Niched Pareto Genetic Algorithm and the Nondominated Sorting Genetic Algorithm over a diverse suite of six test functions. Results are analyzed and presented using techniques that reduce the attainment surfaces generated from several optimization runs into a set of univariate distributions. This allows

Multiobjective Optimal Reactive Power Flow Using Elitist Nondominated Sorting Genetic Algorithm: Comparison and Improvement

by Zhihuan Li, Yinhong Li, Xianzhong Duan
"... Abstract – Elitist nondominated sorting genetic algorithm (NSGA-II) is adopted and improved for multiobjective optimal reactive power flow (ORPF) problem. Multiobjective ORPF, formulated as a multiobjective mixed integer nonlinear optimization problem, minimizes real power loss and improves voltage ..."
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Abstract – Elitist nondominated sorting genetic algorithm (NSGA-II) is adopted and improved for multiobjective optimal reactive power flow (ORPF) problem. Multiobjective ORPF, formulated as a multiobjective mixed integer nonlinear optimization problem, minimizes real power loss and improves voltage

Elitist multiobjective evolutionary algorithm for environmental/economic dispatch

by Robert T. F. Ah King, Harry C. S. Rughooputh - in IEEE Congress on Evolutionary Computation , 2003
"... Abstract- The environmentalleconomic dispatch problem is a multiobjective nonlinear optimization problem with constraints. Until recently, this problem has been addressed by considering economic and emission objectives separately or as a weighted sum of both objectives. Multiobjective evolutionary a ..."
Abstract - Cited by 7 (1 self) - Add to MetaCart
algorithms can find multiple Pareto-optimal solutions in one single run and this ability makes them attractive for solving problems with multiple and conflicting objectives. This paper uses an elitist multiobjective evolutionary algorithm based on the Non-dominated Sorting Genetic Algorithm- 11 (NSGA-11

Mechanical component design for multiple objectives using elitist non-dominated sorting GA

by Kalyanmoy Deb, Amrit Pratap, Subrajyoti Moitra - Proceedings of the Parallel Problem Solving from Nature VI Conference , 2000
"... Abstract. In this paper, we apply an elitist multi-objective genetic algorithm for solving mechanical component design problems with multiple objectives. Although there exists a number of classical techniques, evolutionary algorithms (EAs) have an edge over the classical methods in that they can fin ..."
Abstract - Cited by 11 (1 self) - Add to MetaCart
find multiple Pareto-optimal solutions in one single simulation run. The proposed algorithm (we call NSGA-II) is a much improved version of the originally proposed nondominated sorting GA (NSGA) in that it is computationally faster, uses an elitist strategy, and it does not require fixing any niching

Elitist Multiobjective Evolutionary Algorithm for Environmental/Economic Dispatch

by unknown authors
"... Abstract- The environmental/economic dispatch problem is a multiobjective nonlinear optimization problem with constraints. Until recently, this problem has been addressed by considering economic and emission objectives separately or as a weighted sum of both objectives. Multiobjective evolutionary a ..."
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algorithms can find multiple Pareto-optimal solutions in one single run and this ability makes them attractive for solving problems with multiple and conflicting objectives. This paper uses an elitist multiobjective evolutionary algorithm based on the Non-dominated Sorting Genetic Algorithm – II (NSGA

Non-dominated ranked genetic algorithm for Solving multiobjective optimization Problems

by Omar Al Jadaan, Lakishmi Rajamani, C. R. Rao - NRGA”, Journal of Theoretical and Applied Information Technology , 2008
"... Multi-objective evolutionary algorithms (EAs) that use non-dominated sorting and sharing have been 3 criticized. Mainly for their: 1- O ( MN) computational complexity (where M is the number of objectives and N is the population size). 2- Non-elitism approach; 3-the need for specifying a sharing para ..."
Abstract - Cited by 5 (0 self) - Add to MetaCart
parameter. In this paper, a method combining the new Ranked based Roulette Wheel selection algorithm with Pareto-based population ranking Algorithm is proposed, named Non-dominated Ranking Genetic Algorithm (NRGA), which alleviates most of the above three difficulties. A two tier ranked based roulette wheel

A Nondominated Sorting Genetic Algorithm for Bi-Objective Network Coding Based Multicast Routing Problems

by Huanlai Xing, Rong Qu
"... Abstract — Network coding is a new communication technique that generalizes routing, where, instead of simply forwarding the packets they receive, intermediate nodes are allowed to recombine (code) together some of the data packets received from different incoming links if necessary. By doing so, th ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
-objective optimization problem to minimize the total cost and the maximum transmission delay of a multicast. This bi-objective optimization problem has not been considered in the literature. We adapt the Elitist Nondominated Sorting Genetic Algorithm (NSGA-II) for the new problem by introducing two adjustments

A Nondominated Sorting Genetic Algorithm for Sustainable Reverse Logistics Network Design

by Mohammad Asghari , Samaneh Nezhadali
"... Abstract Determining the appropriate strategy in recycling method that will has less pollution besides the economical process, has been signified as one of the basic principles for achieving sustainability in the supply chain due to the new legislation, environmental concerns' growth, increase ..."
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for the design and strategic planning of a sustainable chain. Due to the complexity and differences in the nature of the model objectives, is proposed a heuristic method based nondominated sorting genetic algorithm to solve the problem. Finally, the results are discussed and analyzed.
Results 1 - 10 of 154