Krzysztof Krawiec


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We propose that the development of standardized, explicit, machine-readable descriptions of metaheuris- tics will greatly advance scientific progress in the field. In particular, we advocate a purely functional description of metaheuristics --- separate from any metaphors that inspire them and with no hidden mech- anisms. A recent policy statement in the Journal of Heuristics1 highlights the need for improved research practice via increased transparency of implementation and principled decomposition of metaheuristics to isolate the contribution of their component parts. We argue here that addressing these issues via explicit descriptions can also offer further benefits. Standardization and pure-functional descriptions promote a higher standard of rigor for both communication and reproducibility of results. The modularity of our proposed approach opens up opportunities to compose heuristics in novel ways, along with better support for parallel processing. Most significantly, it is the basis for a greater degree of mechanized reasoning: we discuss how this might support large-scale collaborative research activity, leading to automated dis- covery, mining and assembly of metaheuristics.

@INPROCEEDINGS { Swan2015:MIC,
    ABSTRACT = { We propose that the development of standardized, explicit, machine-readable descriptions of metaheuris- tics will greatly advance scientific progress in the field. In particular, we advocate a purely functional description of metaheuristics --- separate from any metaphors that inspire them and with no hidden mech- anisms. A recent policy statement in the Journal of Heuristics1 highlights the need for improved research practice via increased transparency of implementation and principled decomposition of metaheuristics to isolate the contribution of their component parts. We argue here that addressing these issues via explicit descriptions can also offer further benefits. Standardization and pure-functional descriptions promote a higher standard of rigor for both communication and reproducibility of results. The modularity of our proposed approach opens up opportunities to compose heuristics in novel ways, along with better support for parallel processing. Most significantly, it is the basis for a greater degree of mechanized reasoning: we discuss how this might support large-scale collaborative research activity, leading to automated dis- covery, mining and assembly of metaheuristics. },
    AUTHOR = { Jerry Swan and Steven Adriaensen and Mohamed Bishr and Edmund K Burke and John A Clark and Patrick De Causmaecker and Juanjo Durillo and Kevin Hammond and Emma Hart and Colin G Johnson and Zoltan A Kocsis and Ben Kovitz and Krzysztof Krawiec and Simon Martin and JJ Merelo and Leandro L Minku and Ender Ozcan and Gisele L Pappa and Erwin Pesch and Pablo Garcıa-S{\'a}nchez and Andrea Schaerf and Kevin Sim and Jim E Smith and Thomas St{\"u}tzle and Stefan Vo{\ss} and Stefan Wagner and Xin Yao },
    BOOKTITLE = { MIC 2015: The XI Metaheuristics International Conference },
    LOCATION = { Agadir, Morocco },
    MONTH = { June },
    TITLE = { A Research Agenda for Metaheuristic Standardization },
    YEAR = { 2015 },
}


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