Proactive selection of metaheuristics based on knowledge of previous results
Alejandro Rosete-Suárez, Mailyn Moreno-Espino
Available Online October 2013.
- https://doi.org/10.2991/.2013.14How to use a DOI?
- metaheuristic, agents, proactive behavior
- This paper presents two proactive algorithms that act as meta-metaheuristic agents: they decide which metaheuristic will be used to solve a new problem. These meta-metaheuristic agents operate in the environment of iterative work on optimizing problems, with the goal of selecting good metaheuristics to solve new problems. The information about previous results is converted into ex-plicit knowledge that is used by the meta-metaheuristic agents to decide the most adequate metaheuristics. This proactive decision is based on a fuzzy vector that de-scribes each problem. The proposal has been validated through experimentation with 28 functions on binary strings.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Alejandro Rosete-Suárez AU - Mailyn Moreno-Espino PY - 2013/10 DA - 2013/10 TI - Proactive selection of metaheuristics based on knowledge of previous results BT - Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support PB - Atlantis Press SP - 111 EP - 119 SN - 1951-6851 UR - https://doi.org/10.2991/.2013.14 DO - https://doi.org/10.2991/.2013.14 ID - Rosete-Suárez2013/10 ER -