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Dynamic Problems and Nature Inspired Meta-heuristics
| Content Provider | CiteSeerX |
|---|---|
| Abstract | Abstract: Biological systems are, by their very nature, adaptive. However, the meta-heuristic search algorithms inspired by them have mainly been applied to static prob-lems (i.e., problems that do not change while they are being solved). Recently, a greater body of work has been com-pleted on the newer meta-heuristics, particularly ant colony optimisation, particle swarm optimisation and extremal optimisation. This survey paper examines representative works and methodologies of these techniques on this class of problems. Beyond this we outline the limitations of these methods. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Dynamic Problem Nature Inspired Meta-heuristics Meta-heuristic Search Algorithm Ant Colony Optimisation Static Prob-lems Particle Swarm Optimisation Survey Paper Examines Representative Work Biological System Extremal Optimisation |
| Content Type | Text |
| Resource Type | Article |
