A criterion-space branch-reduction-bound algorithm for solving generalized multiplicative problems

In this paper, we investigate a generalized multiplicative problem (GMP) that is known to be NP-hard even with one linear product term. We first introduce some criterion-space variables to obtain an equivalent problem of the GMP. A criterion-space branch-reduction-bound algorithm is then designed, w...

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Vydáno v:Journal of global optimization Ročník 89; číslo 3; s. 597 - 632
Hlavní autoři: Jiao, Hongwei, Li, Binbin, Yang, Wenqiang
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.07.2024
Springer
Springer Nature B.V
Témata:
Algorithms
Approximation
Backup software
Bond portfolios
Computer Science
Criteria
Design
Investment analysis
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Optimization algorithms
Real Functions
Variables
Criterion-space region reduction technologies
Global optimization
Computational complexity
Generalized multiplicative problems
Branch-reduction-bound algorithm
ISSN:0925-5001, 1573-2916
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Shrnutí:In this paper, we investigate a generalized multiplicative problem (GMP) that is known to be NP-hard even with one linear product term. We first introduce some criterion-space variables to obtain an equivalent problem of the GMP. A criterion-space branch-reduction-bound algorithm is then designed, which integrates some basic operations such as the two-level linear relaxation technique, rectangle branching rule and criterion-space region reduction technologies. The global convergence of the presented algorithm is proved by means of the subsequent solutions of a series of linear relaxation problems, and its maximum number of iterations is estimated on the basis of exhaustiveness of branching rule. Finally, numerical results demonstrate the presented algorithm can efficiently find the global optimum solutions for some test instances with the robustness.
Bibliografie:ObjectType-Article-1
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ISSN:0925-5001
1573-2916
DOI:10.1007/s10898-023-01358-w