No free lunch theorems for optimization
Datos Bibliográficos
| ID | 23367199 |
|---|---|
| Autores | David H Wolpert (0000-0003-3105-2869, IBM Research - Almaden), William G Macready (Santa Fe Institute) |
| Año | 1997 |
| Volumen | 1 |
| Número | 1 |
| Páginas | 67-82 |
| Fecha de publicación | 1997-04-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | IEEE Transactions on Evolutionary Computation (JOURNAL) |
| Identificadores de la revista | ISSN: 1089-778X • E-ISSN: 1941-0026 |
| Editorial | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/4235.585893 |
| OpenAlex | W2151554678 |
| Idioma | EN |
| Citas recibidas | 67 |
| Referencias citadas | 10 |
A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving. A number of "no free lunch" (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performance over another class. These theorems result in a geometric interpretation of what it means for an algorithm to be well suited to an optimization problem. Applications of the NFL theorems to information-theoretic aspects of optimization and benchmark measures of performance are also presented. Other issues addressed include time-varying optimization problems and a priori "head-to-head" minimax distinctions between optimization algorithms, distinctions that result despite the NFL theorems' enforcing of a type of uniformity over all algorithms.
A priori and a posteriori · Algorithm · Class (philosophy) · Continuous optimization · Interpretation (philosophy) · L-reduction · Mathematical optimization · Minimax · Multi-swarm optimization · Optimization problem · Advanced Bandit Algorithms Research · Advanced Optimization Algorithms Research · Artificial Intelligence · Computer Science · Mathematics · Metaheuristic Optimization Algorithms Research
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| Obras citantes distintas | 67 |
|---|---|
| Citas por año | 3,05 |
| Intervalo de citas | 2004 - 2026 (23) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 62 |