IEICE TRANSACTIONS on Fundamentals
Modular Approach for Solving Nonlinear Knapsack Problems
Summary :
This paper develops an algorithm based on the Modular Approach to solve singly constrained separable discrete optimization problems (Nonlinear Knapsack Problems). The Modular Approach uses fathoming and integration techniques repeatedly. The fathoming reduces the decision space of variables. The integration reduces the number of variables in the problem by combining several variables into one variable. Computational experiments for "hard" test problems with up to 1000 variables are provided. Each variable has up to 1000 integer values.
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- IEICE TRANSACTIONS on Fundamentals Vol.E82-A No.9 pp.1860-1864
- Publication Date
- 1999/09/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Section on Nonlinear Theory and Its Applications)
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Yuji NAKAGAWA, Akinori IWASAKI, "Modular Approach for Solving Nonlinear Knapsack Problems" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 9, pp. 1860-1864, September 1999, doi: .
Abstract: This paper develops an algorithm based on the Modular Approach to solve singly constrained separable discrete optimization problems (Nonlinear Knapsack Problems). The Modular Approach uses fathoming and integration techniques repeatedly. The fathoming reduces the decision space of variables. The integration reduces the number of variables in the problem by combining several variables into one variable. Computational experiments for "hard" test problems with up to 1000 variables are provided. Each variable has up to 1000 integer values.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_9_1860/_p
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@ARTICLE{e82-a_9_1860,
author={Yuji NAKAGAWA, Akinori IWASAKI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Modular Approach for Solving Nonlinear Knapsack Problems},
year={1999},
volume={E82-A},
number={9},
pages={1860-1864},
abstract={This paper develops an algorithm based on the Modular Approach to solve singly constrained separable discrete optimization problems (Nonlinear Knapsack Problems). The Modular Approach uses fathoming and integration techniques repeatedly. The fathoming reduces the decision space of variables. The integration reduces the number of variables in the problem by combining several variables into one variable. Computational experiments for "hard" test problems with up to 1000 variables are provided. Each variable has up to 1000 integer values.},
keywords={},
doi={},
ISSN={},
month={September},}
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TY - JOUR
TI - Modular Approach for Solving Nonlinear Knapsack Problems
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1860
EP - 1864
AU - Yuji NAKAGAWA
AU - Akinori IWASAKI
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 1999
AB - This paper develops an algorithm based on the Modular Approach to solve singly constrained separable discrete optimization problems (Nonlinear Knapsack Problems). The Modular Approach uses fathoming and integration techniques repeatedly. The fathoming reduces the decision space of variables. The integration reduces the number of variables in the problem by combining several variables into one variable. Computational experiments for "hard" test problems with up to 1000 variables are provided. Each variable has up to 1000 integer values.
ER -
English
