Name
Title | ||
|---|---|---|
An adaptive strategy for updating the memory in Evolutionary Algorithms for dynamic optimization |
Abstract | ||
|---|---|---|
The memory scheme is one of the most widely employed techniques in Evolutionary Algorithms for solving dynamic optimization problems. The updating strategy is a key concern for the memory scheme. Unfortunately, the existent memory updating strategies neglect the characteristics of the memory updating behaviors, and sometimes this could lead results against the original intention. In this paper, a novel updating strategy is proposed, which can adaptively update the memory according to the characteristics of the memory updating behaviors. Experiments are carried out in different kinds of dynamic environments, and the experimental results show that the proposed strategy is better than the traditional strategies. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CIDUE.2011.5948487 | CIDUE |
Keywords | Field | DocType |
dynamic optimization problem,evolutionary algorithm,evolutionary computation,memory updating strategy,evolutionary algorithms,updating strategy,dynamic optimization,adaptive updating strategy,memory scheme,associative memory,memory management,optimization,redundancy,generators | Content-addressable memory,Adaptive strategies,Evolutionary algorithm,Computer science,Evolutionary computation,Memory management,Redundancy (engineering),Artificial intelligence,Optimization problem,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4244-9930-4 | 6 | 0.44 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tao Zhu | 1 | 82 | 14.36 |
| Wenjian Luo | 2 | 356 | 40.95 |
| Zhifang Li | 3 | 15 | 2.45 |