Performance of simulated annealing-based heuristic for the unconstrained binary quadratic programming problem

The unconstrained binary quadratic programming problem (BQP) is known to be NP-hard and has many practical applications. This paper presents a simulated annealing (SA)-based heuristic for the BQP. The new SA heuristic for the BQP is based on a simple (1-opt) local search heuristic and designed with...

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Bibliographic Details
Published in:European journal of operational research Vol. 134; no. 1; pp. 103 - 119
Main Authors: Katayama, Kengo, Narihisa, Hiroyuki
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.10.2001
Elsevier
Elsevier Sequoia S.A
Series:European Journal of Operational Research
Subjects:
ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary:The unconstrained binary quadratic programming problem (BQP) is known to be NP-hard and has many practical applications. This paper presents a simulated annealing (SA)-based heuristic for the BQP. The new SA heuristic for the BQP is based on a simple (1-opt) local search heuristic and designed with a simple cooling schedule, but the multiple annealing processes are adopted. To show practical performances of the SA, we test on publicly available benchmark instances of large size ranging from 500 to 2500 variables and compare them with other heuristics such as multi-start local search, the previous SA, tabu search, and genetic algorithm incorporating the 1-opt local search. Computational results indicate that our SA leads to high-quality solutions with short times and is more effective than the competitors particularly for the largest benchmark set. Furthermore, the values of new best-known solutions found by the SA for several large instances are also reported.
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ISSN:0377-2217
1872-6860
DOI:10.1016/S0377-2217(00)00242-3