Most common heuristics are restricted to static optimization problems, i.e. problems that are completely known to the optimization algorithm from the beginning. However, many real-world optimization problems are stochastic and change over time. Therefore, powerful heuristics are needed that are not only capable of finding good solutions to a single static problem, but that account for the dynamics and the uncertainty present in real world problems.
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- Summary and Outlook
- Springer US
- Chapter 10