An empirical study on the synergy of multiple crossover operators
Typical evolutionary algorithms (EAs) exploit the different space-search properties of variation operators, such as crossover, mutation and local optimization. There are also various operators in each element. This paper provides an extensive empirical study on the synergy among multiple crossover o...
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| Veröffentlicht in: | IEEE transactions on evolutionary computation 2002-04, Vol.6 (2), p.212-223 |
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| container_title | IEEE transactions on evolutionary computation |
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| creator | YOON, Hyun-Sook MOON, Byung-Ro |
| description | Typical evolutionary algorithms (EAs) exploit the different space-search properties of variation operators, such as crossover, mutation and local optimization. There are also various operators in each element. This paper provides an extensive empirical study on the synergy among multiple crossover operators. We choose a number of different crossover operators in an EA and investigate whether or not their combinations outperform the sole usage of the best crossover operator. The traveling salesman problem and the graph bisection problem were chosen for experimentation. Strong synergy effects were observed in both problems. |
| doi_str_mv | 10.1109/4235.996022 |
| format | Article |
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There are also various operators in each element. This paper provides an extensive empirical study on the synergy among multiple crossover operators. We choose a number of different crossover operators in an EA and investigate whether or not their combinations outperform the sole usage of the best crossover operator. The traveling salesman problem and the graph bisection problem were chosen for experimentation. Strong synergy effects were observed in both problems.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science</subject><subject>Computer science; control theory; systems</subject><subject>Connectionism. Neural networks</subject><subject>Crossovers</subject><subject>Empirical analysis</subject><subject>Evolutionary algorithms</subject><subject>Evolutionary computation</subject><subject>Exact sciences and technology</subject><subject>Experimentation</subject><subject>Flows in networks. 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| ispartof | IEEE transactions on evolutionary computation, 2002-04, Vol.6 (2), p.212-223 |
| issn | 1089-778X 1941-0026 |
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| source | IEEE Electronic Library (IEL) |
| subjects | Applied sciences Artificial intelligence Computer science Computer science control theory systems Connectionism. Neural networks Crossovers Empirical analysis Evolutionary algorithms Evolutionary computation Exact sciences and technology Experimentation Flows in networks. Combinatorial problems Genetic algorithms Genetic mutations Local optimization Moon Mutations Operational research and scientific management Operational research. Management science Operators Probability Sole Steady-state Testing Traveling salesman problems Very large scale integration |
| title | An empirical study on the synergy of multiple crossover operators |
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