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## Evolutionary Algorithms for Non-Stationary Environments (1999)

Venue: | In Proc. of 8th Workshop: Intelligent Information systems |

Citations: | 16 - 0 self |

### Citations

2762 |
Genetic Algorithms + Data Structures = Evolution Programs
- Michalewicz
- 1996
(Show Context)
Citation Context ...second class of problems many constraint-handling methods (e.g., methods based on preserving feasibility of solutions, penalty functions, repair algorithms, specialized operators, etc.) were proposed =-=[24]-=-. Clearly, the largest effort of the researchers of evolutionary computation community has been focused exclusively on these two classes of problems. However, as discussed in Introduction, most real-w... |

1090 |
An Analysis of the Behavior of a Class of Genetic Adaptive Systems
- Jong
- 1975
(Show Context)
Citation Context ...ature of the search process and the presence of continuously modified and improved population of solutions. One of the first measures were on-line and off-line performance proposed by De Jong in 1975 =-=[7]-=-. -- off-line performance --- is the best value in the current population averaged over the entire run. It represents the efficiency of the algorithm in the given time of run. -- on-line performance -... |

821 | Tabu Search
- Glover, Laguna
- 1997
(Show Context)
Citation Context ... of efficiency in dynamic optimization is adding memory structures to the algorithm. One of the earliest forms of memory although not used for non-stationary optimization was the tabu-search strategy =-=[12, 13]-=-. Beside TS a considerable number of other ideas using past experience and the forms of memory were proposed. We can classify them into several types [30]: ffl numerical memory --- where the modificat... |

635 |
Genetic algorithms with sharing for multimodel function optimization,
- Goldberg, Richardson
- 1987
(Show Context)
Citation Context ...e maintaining diversity of the population could increase search performance of the algorithm. Among many maintaining population diversity techniques we can select: ffl sharing and crowding techniques =-=[15, 4]-=-, ffl techniques based on the concepts of temperature and entropy [25, 26], ffl techniques based on the concept of the age of individuals [10], ffl a random immigrants mechanism [5, 16], ffl a mechani... |

365 | Parameter control in evolutionary algorithms.
- Eiben, Hinterding, et al.
- 1999
(Show Context)
Citation Context ...he algorithm to the non-stationary environment is the next feature of the efficient optimization. So adaptive and self-adaptive techniques are the next significant extension of evolutionary algorithm =-=[1, 3, 8]-=-. In adaptation the parameters of the algorithm are updated using statistic or heuristic rules to determine how to update. Update of the parameters in the genetic process in parallel with searching of... |

145 |
Nonstationary function optimization using genetic algorithms with dominance and diploidy
- Goldberg, Smith
- 1987
(Show Context)
Citation Context ... guide search operators. 8 K. Trojanowski, Z. Michalewicz ffl exact memory --- where existing structures are enhanced by additional genes, chromosomes (diploidy) or groups of chromosomes (polyploidy) =-=[6, 14, 17, 20, 23, 25, 28, 35]-=-. The memory is utilized during the search process and between the search tasks as well. Change of the current active chromosome of the individual by the data from memory is controlled by some dominan... |

139 | On the use of nonstationary penalty functions to solve constrained optimization problems with genetic algorithms,” - Joines, Houk - 1994 |

113 | Genetic algorithms for tracking changing environments,”
- Cobb, Grefenstette
- 1993
(Show Context)
Citation Context ...ing techniques [15, 4], ffl techniques based on the concepts of temperature and entropy [25, 26], ffl techniques based on the concept of the age of individuals [10], ffl a random immigrants mechanism =-=[5, 16]-=-, ffl a mechanism of variable range local search around the current locations [32]. ffi Adaptation and self-adaptation mechanism. Dynamical adjustment of the algorithm to the non-stationary environmen... |

97 | Constrained optimization via genetic algorithms, Simulation 62(4 - Homaifar, Qi, et al. - 1994 |

77 | Nonstationary Function Optimization using the Structured Genetic Algorithm. Parallel Problem Solving from
- Dasgupta, McGregor
- 1992
(Show Context)
Citation Context ... guide search operators. 8 K. Trojanowski, Z. Michalewicz ffl exact memory --- where existing structures are enhanced by additional genes, chromosomes (diploidy) or groups of chromosomes (polyploidy) =-=[6, 14, 17, 20, 23, 25, 28, 35]-=-. The memory is utilized during the search process and between the search tasks as well. Change of the current active chromosome of the individual by the data from memory is controlled by some dominan... |

72 |
A new diploid scheme and dominance change mechanism for non-stationary function optimization”,
- Ng, Wong
- 1995
(Show Context)
Citation Context ...In other publications authors visually compared graphs of the best objective function value measured during the entire search process (or graphs of the mean value obtained from series of experiments) =-=[1, 3, 5, 4, 6, 10, 14, 16, 22, 25, 26, 27, 33]-=-. In some papers graphs of average values of all individuals or of the worst individual in the population were also analyzed [5, 14, 6, 25, 26]. Both these methods were based on the measures of off-li... |

69 | Intelligent mutation rate control in canonical genetic algorithms.
- Back, Schutz
- 1996
(Show Context)
Citation Context ...he algorithm to the non-stationary environment is the next feature of the efficient optimization. So adaptive and self-adaptive techniques are the next significant extension of evolutionary algorithm =-=[1, 3, 8]-=-. In adaptation the parameters of the algorithm are updated using statistic or heuristic rules to determine how to update. Update of the parameters in the genetic process in parallel with searching of... |

67 | A comparison of dominance mechanisms and simple mutation on non-stationary problems
- Lewis, Hart, et al.
- 1998
(Show Context)
Citation Context ...In other publications authors visually compared graphs of the best objective function value measured during the entire search process (or graphs of the mean value obtained from series of experiments) =-=[1, 3, 5, 4, 6, 10, 14, 16, 22, 25, 26, 27, 33]-=-. In some papers graphs of average values of all individuals or of the worst individual in the population were also analyzed [5, 14, 6, 25, 26]. Both these methods were based on the measures of off-li... |

60 | Tracking Extrema in Dynamic Environments,
- Angeline
- 1997
(Show Context)
Citation Context ...he algorithm to the non-stationary environment is the next feature of the efficient optimization. So adaptive and self-adaptive techniques are the next significant extension of evolutionary algorithm =-=[1, 3, 8]-=-. In adaptation the parameters of the algorithm are updated using statistic or heuristic rules to determine how to update. Update of the parameters in the genetic process in parallel with searching of... |

55 |
On the behavior of evolutionary algorithms in dynamic environments
- Bäck
- 1998
(Show Context)
Citation Context ... the entire run. It shows the impact of the population on the focus of the search. These two measures, although designed for static environments, were employed in experiments with non-stationary ones =-=[2, 16, 32, 33]-=-. In other publications authors visually compared graphs of the best objective function value measured during the entire search process (or graphs of the mean value obtained from series of experiments... |

52 | Critical Event Tabu Search for Multidimensional Knapsack Problems, In: Meta-Heuristics: - Glover, Kochenberger - 1996 |

44 |
Adaptation to a changing environment by means of memory based thermodynamical genetic algorithm.
- Mori, Imanishi, et al.
- 1997
(Show Context)
Citation Context ...ce of the algorithm. Among many maintaining population diversity techniques we can select: ffl sharing and crowding techniques [15, 4], ffl techniques based on the concepts of temperature and entropy =-=[25, 26]-=-, ffl techniques based on the concept of the age of individuals [10], ffl a random immigrants mechanism [5, 16], ffl a mechanism of variable range local search around the current locations [32]. ffi A... |

38 | On the use of niching for dynamic landscapes.
- Cedeno, Vemuri
- 1997
(Show Context)
Citation Context ...e maintaining diversity of the population could increase search performance of the algorithm. Among many maintaining population diversity techniques we can select: ffl sharing and crowding techniques =-=[15, 4]-=-, ffl techniques based on the concepts of temperature and entropy [25, 26], ffl techniques based on the concept of the age of individuals [10], ffl a random immigrants mechanism [5, 16], ffl a mechani... |

35 | Solving similar problems using genetic algorithms and case-based memory
- Louis, Johnson
- 1997
(Show Context)
Citation Context ... guide search operators. 8 K. Trojanowski, Z. Michalewicz ffl exact memory --- where existing structures are enhanced by additional genes, chromosomes (diploidy) or groups of chromosomes (polyploidy) =-=[6, 14, 17, 20, 23, 25, 28, 35]-=-. The memory is utilized during the search process and between the search tasks as well. Change of the current active chromosome of the individual by the data from memory is controlled by some dominan... |

32 | A segregated genetic algorithm for constrained structural optimization - Riche, Knopf-Lenoir, et al. - 1995 |

26 | Function optimization in nonstationary environment using steady state genetic algorithms with aging individuals.
- Ghosh, Tsutsui, et al.
- 1998
(Show Context)
Citation Context ...ues we can select: ffl sharing and crowding techniques [15, 4], ffl techniques based on the concepts of temperature and entropy [25, 26], ffl techniques based on the concept of the age of individuals =-=[10]-=-, ffl a random immigrants mechanism [5, 16], ffl a mechanism of variable range local search around the current locations [32]. ffi Adaptation and self-adaptation mechanism. Dynamical adjustment of the... |

22 |
Adaptation to a changing environment by means of the feedback themodynamic genetic algorithms.
- Mori, Kita, et al.
- 1998
(Show Context)
Citation Context ...ce of the algorithm. Among many maintaining population diversity techniques we can select: ffl sharing and crowding techniques [15, 4], ffl techniques based on the concepts of temperature and entropy =-=[25, 26]-=-, ffl techniques based on the concept of the age of individuals [10], ffl a random immigrants mechanism [5, 16], ffl a mechanism of variable range local search around the current locations [32]. ffi A... |

21 | Comparison of steady state and generational genetic algorithms for use in nonstationary environments
- VAVAK, FOGARTY
- 1996
(Show Context)
Citation Context ... the entire run. It shows the impact of the population on the focus of the search. These two measures, although designed for static environments, were employed in experiments with non-stationary ones =-=[2, 16, 32, 33]-=-. In other publications authors visually compared graphs of the best objective function value measured during the entire search process (or graphs of the mean value obtained from series of experiments... |

19 |
A diploid genetic algorithm for preserving population diversity”,
- Yoshida, Adachi
- 1994
(Show Context)
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18 |
Supporting polyploidy in genetic algorithms using dominance vectors,” in Evolutionary Programming
- Hadad, Eick
- 1997
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17 | Toward civilized evolution: Developing inhibitions
- Sebag, Schoenauer, et al.
- 1997
(Show Context)
Citation Context ...optimization was the tabu-search strategy [12, 13]. Beside TS a considerable number of other ideas using past experience and the forms of memory were proposed. We can classify them into several types =-=[30]-=-: ffl numerical memory --- where the modification of algorithm parameters is performed using experience of previous generations [29, 30, 34]. This type of memory has a form of additional numerical par... |

16 |
Knowledge-based selfadaptation in evolutionary search,”
- Chung, Reynolds
- 2000
(Show Context)
Citation Context ...ms of memory were proposed. We can classify them into several types [30]: ffl numerical memory --- where the modification of algorithm parameters is performed using experience of previous generations =-=[29, 30, 34]-=-. This type of memory has a form of additional numerical parameters. They are updated every generation using the results of the previous search. Their influence on the search process is realized by mo... |

10 |
Shared memory based cooperative coevolution
- Puppala, Sen, et al.
- 1998
(Show Context)
Citation Context |

10 |
Learning the local search range for Genetic Optimization in Nonstationary Environments
- Vavak, Jukes, et al.
- 1997
(Show Context)
Citation Context ...lf. The most intuitive form of changes detection in evolutionary algorithms is the observation of population performance. E.g., the time averaged performance of the whole population was controlled in =-=[32]-=-: a significant decrease of the performance was a signal that a change occurred, so it is time to perform some additional steps to recapture the near-optimum solution. Ev. Alg. for Non-stationary Envi... |

6 |
Benchmarks for testing evolutionary algorithms
- Feng, Brune, et al.
- 1997
(Show Context)
Citation Context ...lg. for Non-stationary Environments 9 This formula was later modified slightly to: I = 1 Tmax Tmax X i=1 ff f best (t) f opt (t) ff = ae 1; if f best (t) = f opt (t) 0:5; if f best (t) ! f opt (t) In =-=[9]-=- two benchmarks measuring relative closeness of the best found solution to the global optimum were proposed: Optimality Op and Accuracy Ac. Optimality Op represents closeness of the value of the best ... |

6 | Inductive learning of mutation step-size in evolutionary parameter optimization
- Sebag, Schoenauer, et al.
- 1997
(Show Context)
Citation Context ... ffl symbolic memory --- where the algorithm gradually learns from the individuals in the populations and thus constructs beliefs about the relevance of schemas (Machine Learning theory is exploited) =-=[31]-=-. The symbolic type of memory encodes some knowledge in its structures which have a form of rules used to guide search operators. 8 K. Trojanowski, Z. Michalewicz ffl exact memory --- where existing s... |

5 |
Genetic Algorithms for changing environments”,Proceedings of Parallel Problem Solving From Nature
- Grefenstette
- 1992
(Show Context)
Citation Context ...ing techniques [15, 4], ffl techniques based on the concepts of temperature and entropy [25, 26], ffl techniques based on the concept of the age of individuals [10], ffl a random immigrants mechanism =-=[5, 16]-=-, ffl a mechanism of variable range local search around the current locations [32]. ffi Adaptation and self-adaptation mechanism. Dynamical adjustment of the algorithm to the non-stationary environmen... |

2 |
Redundancy of Genotypes as the Way for Some Advanced Operators in Evolutionary Algorithms - Simulation Study", VIVEK A Quarterly in
- Kwasnicka
- 1997
(Show Context)
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1 |
Adaptive Crossover Using Automata", 3PPSN: Parallel Problem Solving from Nature
- White, Oppacher
- 1994
(Show Context)
Citation Context ...ms of memory were proposed. We can classify them into several types [30]: ffl numerical memory --- where the modification of algorithm parameters is performed using experience of previous generations =-=[29, 30, 34]-=-. This type of memory has a form of additional numerical parameters. They are updated every generation using the results of the previous search. Their influence on the search process is realized by mo... |