Abstract
This paper introduces a new algorithm to deal with multi-objective combinatorial and continuous problems. The algorithm is an extension of a previous one designed to deal with single objective combinatorial problems. The original purpose of the single objective version was to study in a rigorous way the properties the search graph of a particular problem needs to hold so that a randomized local search heuristic can find the optimum with high probability. The extension of these results to better understand multi-objective combinatorial problems seems to be a promising line of research. The work presented here is a first small step in this direction. A detailed description of the multi-objective version is presented along with preliminary experimental results on a well known combinatorial problem. The results show that the algorithm has the desired characteristics.
Keywords
- Random Walk
- Schedule Problem
- Local Search
- Flow Time
- Dominance Relation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Brizuela, C.A., Gutiérrez, E. (2005). Multi-objective Go with the Winners Algorithm: A Preliminary Study. In: Coello Coello, C.A., Hernández Aguirre, A., Zitzler, E. (eds) Evolutionary Multi-Criterion Optimization. EMO 2005. Lecture Notes in Computer Science, vol 3410. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31880-4_15
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DOI: https://doi.org/10.1007/978-3-540-31880-4_15
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