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## Comparison of Multiobjective Evolutionary Algorithms: Empirical Results (2000)

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Citations: | 604 - 39 self |

### Citations

10043 | Genetic Algorithms - Goldberg - 1989 |

1699 | A fast and elitist multiobjective genetic algorithm - Deb, Pratap, et al. - 2002 |

1161 | Evolutionary Algorithms in Theory and Practice - Bäck - 1996 |

633 | A fast elitist non–dominated sorting genetic algorithm for multi–objective optimization: Nsga–ii. Parallel Problem Solving from Nature - KALYANMOY, AGRAWAL, et al. - 2000 |

624 | Genetic algorithms with sharing for multimodal function optimization - Goldberg, Richardson - 1987 |

605 | Genetic algorithm for multiobjective optimization: Formulation, discussion, and generalization - Fonseca, Fleming - 1993 |

520 | Multiobjective optimization using nondominated sorting in genetic algorithms
- Srinivas, Deb
- 1994
(Show Context)
Citation Context ... 1991; Hajela and Lin, 1992; Fonseca c 2000 by the Massachusetts Institute of Technology Evolutionary Computation 8(2): 173-195 E. Zitzler, K. Deb, and L. Thiele and Fleming, 1993; Horn et al., 1994; =-=Srinivas and Deb, 1994-=-). Later, these approaches (and variations of them) were successfully applied to various multiobjective optimization problems (Ishibuchi and Murata, 1996; Cunha et al., 1997; Valenzuela-Rendón and Ur... |

498 | Multiple Criteria Optimization: Theory, Computation, and Application - Steuer - 1986 |

485 | An Overview of Evolutionary Algorithms in Multiobjective Optimization
- Fonseca, Fleming
- 1995
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Citation Context ...s): Among the class of criterion selection approaches, the Vector Evaluated Genetic Algorithm (VEGA) (Schaffer, 1984, 1985) has been chosen. Although some serious drawbacks are known (Schaffer, 1985; =-=Fonseca and Fleming, 1995-=-; Horn, 1997), this algorithm has been a strong point of reference up to now. Therefore, it has been included in this investigation. The EA proposed by Hajela and Lin (1992) is based on aggregation se... |

464 |
Multiple objective optimization with vector evaluated genetic algorithms. In Genetic algorithms and their applications
- Schaffer
- 1985
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Citation Context ...he rapidly growing interest in the area of multiobjective EAs take this fact into account. After the first pioneering studies on evolutionary multiobjective optimization appeared in the mid-eighties (=-=Schaffer, 1984-=-, 1985; Fourman,1985) several different EA implementations were proposed in the years 1991–1994 (Kursawe, 1991; Hajela and Lin, 1992; Fonseca c 2000 by the Massachusetts Institute of Technology Evolut... |

456 | Nonlinear Multiobjective Optimization - Miettinen - 1999 |

433 | Evolutionary algorithms for multiobjective optimization: methods and applications - Zitzler - 1999 |

423 | Multiobjective evolutionary algorithms in aeronautical and aerospace engineering - Montaño, Coello, et al. - 2012 |

392 | A niched Pareto genetic algorithm for multiobjective optimization
- Horn, Nafploitis, et al.
- 1994
(Show Context)
Citation Context ...1991–1994 (Kursawe, 1991; Hajela and Lin, 1992; Fonseca c 2000 by the Massachusetts Institute of Technology Evolutionary Computation 8(2): 173-195 E. Zitzler, K. Deb, and L. Thiele and Fleming, 1993; =-=Horn et al., 1994-=-; Srinivas and Deb, 1994). Later, these approaches (and variations of them) were successfully applied to various multiobjective optimization problems (Ishibuchi and Murata, 1996; Cunha et al., 1997; V... |

309 | An investigation of niche and species formation in genetic function optimization - Deb, Goldberg - 1989 |

286 | A comprehensive survey of evolutionary-based multiobjective optimization techniques - Coello - 1999 |

272 | Genetic algorithms, noise, and the sizing of populations - Goldberg, Deb, et al. - 1992 |

269 | Multiobjective Decision Making: Theory and Methodology - Chankong, Haimes - 1983 |

241 | The Gambler’s ruin problem, genetic algorithms, and the sizing of populations - Harik, Cantú-Paz, et al. - 1999 |

226 | Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms I: A Unified Formulation - Fonseca, Fleming - 1998 |

222 | Multiobjective optimization using evolutionary algorithms – a comparative study - Zitzler, Thiele - 1998 |

209 | Simulated binary crossover for continuous search space - Deb, Agrawal - 1995 |

198 | Multi-objective genetic algorithms: Problem difficulties and construction of test problems
- Deb
- 1999
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Citation Context ...oreover, we do not consider maximization or mixed minimization/maximization problems. Each of the test functions defined below is structured in the same manner and consists itself of three functions (=-=Deb, 1999-=-, 216): Minimize subject to where (6) The function is a function of the first decision variable only, is a function of the remaining variables, and the parameters of are the function values of and . T... |

166 |
A multi-objective genetic local search algorithm and its application to flowshop scheduling
- Isibuchi, Murata
- 1998
(Show Context)
Citation Context ...nd L. Thiele and Fleming, 1993; Horn et al., 1994; Srinivas and Deb, 1994). Later, these approaches (and variations of them) were successfully applied to various multiobjective optimization problems (=-=Ishibuchi and Murata, 1996-=-; Cunha et al., 1997; Valenzuela-Rendón and UrestiCharre, 1997; Fonseca and Fleming, 1998; Parks and Miller, 1998). In recent years, some researchers have investigated particular topics of evolutiona... |

161 | The Pareto archived evolution strategy: A new baseline algorithm for multi-objective optimization - Knowles, Corne - 1999 |

148 | Multiobjective function optimization using nondominated sorting genetic algorithms - Srinivas, Deb - 1995 |

141 | Multiobjective optimization using the niched Pareto genetic algorithm,” IlliGAL
- Horn, Nafpliotis
- 1993
(Show Context)
Citation Context ...8b). In particular, the 176 Evolutionary Computation Volume 8, Number 2 Comparison of Multiobjective EAs algorithm presented by Fonseca and Fleming (1993), the Niched Pareto Genetic Algorithm (NPGA) (=-=Horn and Nafpliotis, 1993-=-; Horn et al., 1994), and the Nondominated Sorting Genetic Algorithm (NSGA) (Srinivas and Deb, 1994) appear to have achieved the most attention in the EA literature and have been used in various studi... |

103 | On the performance assessment and comparison of stochastic multiobjective optimizers - Fonseca, Fleming - 1996 |

97 |
Genetic search strategies in multicriterion optimal design. Structural Optimization 4:99–107
- Hajela, Lin
- 1992
(Show Context)
Citation Context ...on evolutionary multiobjective optimization appeared in the mid-eighties (Schaffer, 1984, 1985; Fourman,1985) several different EA implementations were proposed in the years 1991–1994 (Kursawe, 1991; =-=Hajela and Lin, 1992-=-; Fonseca c 2000 by the Massachusetts Institute of Technology Evolutionary Computation 8(2): 173-195 E. Zitzler, K. Deb, and L. Thiele and Fleming, 1993; Horn et al., 1994; Srinivas and Deb, 1994). La... |

74 | Compaction of symbolic layout using genetic algorithms - Fourman - 1985 |

58 | On a Multi-Objective Evolutionary Algorithm and Its Convergence to the Pareto Set - Rudolph - 1998 |

49 |
Tournament selection, niching, and the preservation of diversity
- Oei, Goldberg
- 1991
(Show Context)
Citation Context ...schemes. Furthermore, since fitness sharing may produce chaotic behavior in combination with tournament selection, a slightly modified method is incorporated here, named continuously updated sharing (=-=Oei et al., 1991-=-). As requires a generational selection mechanism, stochastic universal sampling was used in the implementation. 6.2 Simulation Results In Figures 1–6, the nondominated fronts achieved by the differen... |

40 | A spatial predator-prey approach to multi-objective optimization: A preliminary study
- Laumanns, Rudolph, et al.
- 1998
(Show Context)
Citation Context ... Lamont, 1998a; Rudolph, 1998), niching (Obayashi et al., 1998), and elitism (Parks and Miller, 1998; Obayashi et al., 1998), while others have concentrated on developing new evolutionary techniques (=-=Laumanns et al., 1998-=-; Zitzler and Thiele, 1999). For a thorough discussion of evolutionary algorithms for multiobjective optimization, the interested reader is referred to Fonseca and Fleming (1995), Horn (1997), Van Vel... |

37 | G.B.: Evolutionary computation and convergence to a Pareto front - Veldhuizen, Lamont - 1998 |

34 | Multiple Criteria Decision Support in Engineering - Sen, Yang - 1998 |

32 |
Selective Breeding in a Multiobjective Genetic Algorithm
- Parks, Miller
- 1998
(Show Context)
Citation Context ... them) were successfully applied to various multiobjective optimization problems (Ishibuchi and Murata, 1996; Cunha et al., 1997; Valenzuela-Rendón and UrestiCharre, 1997; Fonseca and Fleming, 1998; =-=Parks and Miller, 1998-=-). In recent years, some researchers have investigated particular topics of evolutionary multiobjective search, such as convergence to the Pareto-optimal front (Van Veldhuizen and Lamont, 1998a; Rudol... |

30 | Continuum structural topology design with Genetic Algorithms - Jakiela, Chapman, et al. - 2000 |

30 | Multiobjective Satisfaction within an Interactive Evolutionary Design Environment. Evolutionary Computation - Parmee, Cvetkovic, et al. - 2000 |

23 | A non-generational genetic algorithm for multiobjective optimization - Valenzuela-Rendon, Uresti-Charre - 1997 |

17 | Topological design of structural components using genetic optimization methods,” in Sensitivity Analysis and Optimization with Numerical Methods - Sandgren, Jensen, et al. - 1990 |

15 | Design space exploration using the genetic algorithm - Esbensen, Kuh - 1996 |

11 |
F1.9 multicriteria decision making
- Horn
- 1997
(Show Context)
Citation Context ...ributed trade-off front. Often, different approaches are classified with regard to the first issue, where one can distinguish between criterion selection, aggregation selection, and Pareto selection (=-=Horn, 1997-=-). Methods performing criterion selection switch between the objectives during the selection phase. Each time an individual is chosen for reproduction, potentially a different objective will decide wh... |

10 |
Niching and elitist models for mogas
- Obayashi, Takahashi, et al.
- 1998
(Show Context)
Citation Context ...some researchers have investigated particular topics of evolutionary multiobjective search, such as convergence to the Pareto-optimal front (Van Veldhuizen and Lamont, 1998a; Rudolph, 1998), niching (=-=Obayashi et al., 1998-=-), and elitism (Parks and Miller, 1998; Obayashi et al., 1998), while others have concentrated on developing new evolutionary techniques (Laumanns et al., 1998; Zitzler and Thiele, 1999). For a thorou... |

3 | Genetic algorithm based structural topology design with compliance and topology simplification considerations - Chapman, Jakiela - 1996 |

3 | Genetic algorithms as an approach to con and topology design - Chapman, Saitou, et al. - 1994 |

2 | Adaptive techniques for evolutionary optimum design - Hamada, Schoenauer - 2000 |

2 | Post-processing of the two-dimensional evolutionary structural optimization topologies - Kim, Querin, et al. - 2000 |

1 | Generation and classi of structural topologies with genetic algorithm speciation - Duda, Jakiela - 1997 |

1 | optimization andmultiple constraint handling with evolutionary algorithms—part ii: Application example - Fonseca, J - 1998 |

1 | Evolutionary Computation Volume 8, Number 2 193 - Zitzler, Deb, et al. - 1997 |