DocumentCode
175730
Title
A novel oppositional biogeography-based optimization for combinatorial problems
Author
Qingzheng Xu ; Lemeng Guo ; Na Wang ; Jin Pan ; Lei Wang
Author_Institution
Xi´an Commun. Inst., Xi´an, China
fYear
2014
fDate
19-21 Aug. 2014
Firstpage
412
Lastpage
418
Abstract
In this paper, a novel definition of opposite path is proposed. Its core feature is that the node sequence of candidate paths and the distances between adjacent nodes in the tour are considered simultaneously. In a sense, the path and its corresponding opposite path have the same (or similar, at least) distance from the optimal path in the current population. Based on an accepted framework for employing opposition-based learning, the Oppositional Biogeography-Based Optimization using the Current Optimum, called COOBBO algorithm, is introduced to solve combinatorial problem, such as traveling salesman problems. The performance of COOBBO on 8 benchmark problems is demonstrated and compared with other optimization algorithms. Simulation results illustrate that the excellent performance of our proposed algorithm is attributed to the distinct definition of opposite path.
Keywords
learning (artificial intelligence); travelling salesman problems; COOBBO algorithm; adjacent nodes; candidate paths; combinatorial problems; current optimum; node sequence; opposite path definition; opposition-based learning; oppositional biogeography-based optimization; traveling salesman problems; Algorithm design and analysis; Benchmark testing; Cities and towns; Optimization; Sociology; Statistics; Traveling salesman problems; biogeography-based optimization; discrete domain; opposition-based learning; traveling salesman problems;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2014 10th International Conference on
Conference_Location
Xiamen
Print_ISBN
978-1-4799-5150-5
Type
conf
DOI
10.1109/ICNC.2014.6975871
Filename
6975871
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