Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Fast and Efficient Stochastic Opposition-Based Learning for
  Differential Evolution in Numerical Optimization   A fast and efficient stochastic opposition-based learning (OBL) variant is
proposed in this paper. OBL is a machine learning concept to accelerate the
convergence of soft computing algorithms, which consists of simultaneously
calculating an original solution and its opposite. Recently, a stochastic OBL
variant called BetaCOBL was proposed, which is capable of controlling the
degree of opposite solutions, preserving useful information held by original
solutions, and preventing the waste of fitness evaluations. While it has shown
outstanding performance compared to several state-of-the-art OBL variants, the
high computational cost of BetaCOBL may hinder it from cost-sensitive
optimization problems. Also, as it assumes that the decision variables of a
given problem are independent, BetaCOBL may be ineffective for optimizing
inseparable problems. In this paper, we propose an improved BetaCOBL that
mitigates all the limitations. The proposed algorithm called iBetaCOBL reduces
the computational cost from $O(NP^{2} \cdot D)$ to $O(NP \cdot D)$ ($NP$ and
$D$ stand for population size and a dimension, respectively) using a linear
time diversity measure. Also, the proposed algorithm preserves strongly
dependent variables that are adjacent to each other using multiple exponential
crossover. We used differential evolution (DE) variants to evaluate the
performance of the proposed algorithm. The results of the performance
evaluations on a set of 58 test functions show the excellent performance of
iBetaCOBL compared to ten state-of-the-art OBL variants, including BetaCOBL.

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The categories of this paper are: hep-th
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The categories of this paper are: nucl-th
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The categories of this paper are: astro-ph
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The categories of this paper are: adap-org
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The categories of this paper are: econ
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The categories of this paper are: q-alg
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The categories of this paper are: math-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: cmp-lg
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The categories of this paper are: alg-geom
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The categories of this paper are: nucl-ex
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The categories of this paper are: mtrl-th
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The categories of this paper are: chem-ph
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The categories of this paper are: q-fin
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The categories of this paper are: q-bio
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The categories of this paper are: hep-ph