Path relinking for unconstrained binary quadratic programming

► We devise for the first time two Path Relinking methods for UBQP. ► We assess the performance of these methods on both random and structured benchmark problems. ► The proposed methods improve the previous best known results for almost 40 percent of the 103 MaxCut instances. ► The proposed methods...

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Bibliographic Details
Published in:European journal of operational research Vol. 223; no. 3; pp. 595 - 604
Main Authors: Wang, Yang, Lü, Zhipeng, Glover, Fred, Hao, Jin-Kao
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 16.12.2012
Elsevier
Elsevier Sequoia S.A
Subjects:
Algorithmics. Computability. Computer arithmetics
Algorithms
Applied sciences
Benchmarks
Comparative analysis
Computational efficiency
Computer Science
Computer science; control theory; systems
Effectiveness
Exact sciences and technology
Information retrieval. Graph
Mathematical models
Mathematical problems
Mathematical programming
MaxCut
Operational research
Operational research and scientific management
Operational research. Management science
Path relinking
Quadratic programming
Strategy
Studies
Tabu search
Theoretical computing
UBQP
Path relinking
UBQP
Tabu search
MaxCut
Unconstrained optimization
Zero one programming
Probabilistic approach
Graph cut
Efficiency
Evolutionary algorithm
Combinatorial optimization
Quadratic programming
ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary:► We devise for the first time two Path Relinking methods for UBQP. ► We assess the performance of these methods on both random and structured benchmark problems. ► The proposed methods improve the previous best known results for almost 40 percent of the 103 MaxCut instances. ► The proposed methods match consistently the previous best known results for the 31 large random instances. This paper presents two path relinking algorithms to solve the unconstrained binary quadratic programming (UBQP) problem. One is based on a greedy strategy to generate the relinking path from the initial solution to the guiding solution and the other operates in a random way. We show extensive computational results on five sets of benchmarks, including 31 large random UBQP instances and 103 structured instances derived from the MaxCut problem. Comparisons with several state-of-the-art algorithms demonstrate the efficacy of our proposed algorithms in terms of both solution quality and computational efficiency. It is noteworthy that both algorithms are able to improve the previous best known results for almost 40 percent of the 103 MaxCut instances.
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2012.07.012