Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generating Large-scale Dynamic Optimization Problem Instances Using the
  Generalized Moving Peaks Benchmark   This document describes the generalized moving peaks benchmark (GMPB) and how
it can be used to generate problem instances for continuous large-scale dynamic
optimization problems. It presents a set of 15 benchmark problems, the relevant
source code, and a performance indicator, designed for comparative studies and
competitions in large-scale dynamic optimization. Although its primary purpose
is to provide a coherent basis for running competitions, its generality allows
the interested reader to use this document as a guide to design customized
problem instances to investigate issues beyond the scope of the presented
benchmark suite. To this end, we explain the modular structure of the GMPB and
how its constituents can be assembled to form problem instances with a variety
of controllable characteristics ranging from unimodal to highly multimodal,
symmetric to highly asymmetric, smooth to highly irregular, and various degrees
of variable interaction and ill-conditioning.

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The categories of this paper are: hep-lat
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The categories of this paper are: physics
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The categories of this paper are: nlin
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The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
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The categories of this paper are: bayes-an
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The categories of this paper are: acc-phys
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The categories of this paper are: hep-th
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The categories of this paper are: dg-ga
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The categories of this paper are: funct-an
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The categories of this paper are: hep-ph
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The categories of this paper are: q-bio
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The categories of this paper are: quant-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: adap-org