Optimization with randomized search heuristics—the (A)NFL theorem, realistic scenarios, and difficult functions-Reference-Cited by-同舟云学术

Optimization with randomized search heuristics—the (A)NFL theorem, realistic scenarios, and difficult functions

Published:2002-09 Issue:1 Volume:287 Page:131-144
ISSN:0304-3975
Container-title:Theoretical Computer Science
language:en
Short-container-title:Theoretical Computer Science

Author:

Droste Stefan,Jansen Thomas,Wegener Ingo

Publisher

Elsevier BV

Subject

General Computer Science,Theoretical Computer Science

Reference18 articles.

1. On the futility of blind search: an algorithmic view of no free lunch;Culberson;Evol. Comput.,1998

2. Perhaps not a free lunch but at least a free appetizer;Droste,1999

3. Evolutionary Computation: Toward a New Philosophy of Machine Intelligence;Fogel,1995

4. F. Glover, M. Laguna, Tabu search, in: C. Reeves (Ed.), Modern Heuristic Techniques for Combinatorial Problems, Scientific Publications, Oxford, 1993.

5. Genetic Algorithms in Search, Optimization, and Machine Learning;Goldberg,1989

Cited by 76 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine Learning based Algorithm Selection and Genetic Algorithms for serial-batch scheduling;Computers & Operations Research;2025-01

2. The SLO Hierarchy of pseudo-Boolean Functions and Runtime of Evolutionary Algorithms;Proceedings of the Genetic and Evolutionary Computation Conference;2024-07-14

3. Black eagle optimizer: a metaheuristic optimization method for solving engineering optimization problems;Cluster Computing;2024-06-13

4. Research on Fault Diagnosis of Robot Arm With Dynamic Simulation and Domain Adaptation;IEEE Access;2024

5. A Literature Review and Critical Analysis of Metaheuristics Recently Developed;Archives of Computational Methods in Engineering;2023-07-22