Abstract：
:Choosing a subset of representative items from a set of alternatives is an important problem in many scientific fields such as environmental science and statistics. For most practical problems, however, a computationally efficient solution method is not known to exist. While this problem has attracted a significant amount of attention, the majority of specifically designed algorithms do not scale well with respect to the problem size or do not provide a usable open-source package. In this study, we show that any global continuous optimization technique can be used for solving the representative subset selection problem. The latter is achieved by designing a simple transformation which embeds the problem's discrete space into a larger continuous space. The proposed methodology is applied to design problems in environmental and statistical domains. We evaluate the proposed method using several open-source global optimization packages, and show that this technique compares favorably with existing direct methods.
journal_name
Environ Monit Assessjournal_title
Environmental monitoring and assessmentauthors
Vaisman Rdoi
10.1007/s10661-019-7938-6subject
Has Abstractpub_date
2020-05-13 00:00:00pages
361issue
6eissn
0167-6369issn
1573-2959pii
10.1007/s10661-019-7938-6journal_volume
192pub_type
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